1067:. Shotgun sequencing reveals genes present in environmental samples. Historically, clone libraries were used to facilitate this sequencing. However, with advances in high throughput sequencing technologies, the cloning step is no longer necessary and greater yields of sequencing data can be obtained without this labour-intensive bottleneck step. Shotgun metagenomics provides information both about which organisms are present and what metabolic processes are possible in the community. Because the collection of DNA from an environment is largely uncontrolled, the most abundant organisms in an environmental sample are most highly represented in the resulting sequence data. To achieve the high coverage needed to fully resolve the genomes of under-represented community members, large samples, often prohibitively so, are needed. On the other hand, the random nature of shotgun sequencing ensures that many of these organisms, which would otherwise go unnoticed using traditional culturing techniques, will be represented by at least some small sequence segments.
1482:-based comparative metagenomic analysis application called Community-Analyzer has been developed by Kuntal et al. which implements a correlation-based graph layout algorithm that not only facilitates a quick visualization of the differences in the analyzed microbial communities (in terms of their taxonomic composition), but also provides insights into the inherent inter-microbial interactions occurring therein. Notably, this layout algorithm also enables grouping of the metagenomes based on the probable inter-microbial interaction patterns rather than simply comparing abundance values of various taxonomic groups. In addition, the tool implements several interactive GUI-based functionalities that enable users to perform standard comparative analyses across microbiomes.
1969:
critically important for the health of the intestinal tract. There are two types of functions in these range clusters: housekeeping and those specific to the intestine. The housekeeping gene clusters are required in all bacteria and are often major players in the main metabolic pathways including central carbon metabolism and amino acid synthesis. The gut-specific functions include adhesion to host proteins and the harvesting of sugars from globoseries glycolipids. Patients with irritable bowel syndrome were shown to exhibit 25% fewer genes and lower bacterial diversity than individuals not suffering from irritable bowel syndrome indicating that changes in patients' gut biome diversity may be associated with this condition.
1100:; Ion Torrent PGM System and 454 pyrosequencing typically produces ~400 bp reads, Illumina MiSeq produces 400-700bp reads (depending on whether paired end options are used), and SOLiD produce 25–75 bp reads. Historically, these read lengths were significantly shorter than the typical Sanger sequencing read length of ~750 bp, however the Illumina technology is quickly coming close to this benchmark. However, this limitation is compensated for by the much larger number of sequence reads. In 2009, pyrosequenced metagenomes generate 200–500 megabases, and Illumina platforms generate around 20–50 gigabases, but these outputs have increased by orders of magnitude in recent years.
998:
38:
1427:
MEGAN run slowly to annotate large samples (e.g., several hours to process a small/medium size dataset/sample ). Thus, ultra-fast classifiers have recently emerged, thanks to more affordable powerful servers. These tools can perform the taxonomic annotation at extremely high speed, for example CLARK (according to CLARK's authors, it can classify accurately "32 million metagenomic short reads per minute"). At such a speed, a very large dataset/sample of a billion short reads can be processed in about 30 minutes.
1883:
1870:
high-throughput bioinformatic analysis pipelines. The sequence-driven approach to screening is limited by the breadth and accuracy of gene functions present in public sequence databases. In practice, experiments make use of a combination of both functional and sequence-based approaches based upon the function of interest, the complexity of the sample to be screened, and other factors. An example of success using metagenomics as a biotechnology for drug discovery is illustrated with the
366:
1164:
207:
7807:
743:
321:
1415:(MEta Genome ANalyzer). A first version of the program was used in 2005 to analyse the metagenomic context of DNA sequences obtained from a mammoth bone. Based on a BLAST comparison against a reference database, this tool performs both taxonomic and functional binning, by placing the reads onto the nodes of the NCBI taxonomy using a simple lowest common ancestor (LCA) algorithm or onto the nodes of the
7835:
7795:
1698:. Functional metagenomics strategies are being used to explore the interactions between plants and microbes through cultivation-independent study of these microbial communities. By allowing insights into the role of previously uncultivated or rare community members in nutrient cycling and the promotion of plant growth, metagenomic approaches can contribute to improved disease detection in
1251:. The use of reference genomes allows researchers to improve the assembly of the most abundant microbial species, but this approach is limited by the small subset of microbial phyla for which sequenced genomes are available. After an assembly is created, an additional challenge is "metagenomic deconvolution", or determining which sequences come from which species in the sample.
559:
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1980:(HMP), gut microbial communities were assayed using high-throughput DNA sequencing. HMP showed that, unlike individual microbial species, many metabolic processes were present among all body habitats with varying frequencies. Microbial communities of 649 metagenomes drawn from seven primary body sites on 102 individuals were studied as part of the
858:, it did support early microbial morphology-based observations that diversity was far more complex than was known by culturing methods. Soon after that in 1995, Healy reported the metagenomic isolation of functional genes from "zoolibraries" constructed from a complex culture of environmental organisms grown in the laboratory on dried
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approach is limited by availability of a suitable screen and the requirement that the desired trait be expressed in the host cell. Moreover, the low rate of discovery (less than one per 1,000 clones screened) and its labor-intensive nature further limit this approach. In contrast, sequence-driven analysis uses
1396:) a community resource for metagenome data set analysis. As of June 2012 over 14.8 terabases (14x10 bases) of DNA have been analyzed, with more than 10,000 public data sets freely available for comparison within MG-RAST. Over 8,000 users now have submitted a total of 50,000 metagenomes to MG-RAST. The
1890:
Metagenomics can provide valuable insights into the functional ecology of environmental communities. Metagenomic analysis of the bacterial consortia found in the defecations of
Australian sea lions suggests that nutrient-rich sea lion faeces may be an important nutrient source for coastal ecosystems.
1621:
for eukarya), the only way to access the genetic diversity of the viral community from an environmental sample is through metagenomics. Viral metagenomes (also called viromes) should thus provide more and more information about viral diversity and evolution. For example, a metagenomic pipeline called
1531:
researchers can piece together a metabolic network that goes beyond species boundaries. Such studies require detailed knowledge about which versions of which proteins are coded by which species and even by which strains of which species. Therefore, community genomic information is another fundamental
1465:
Additionally, several studies have also utilized oligonucleotide usage patterns to identify the differences across diverse microbial communities. Examples of such methodologies include the dinucleotide relative abundance approach by
Willner et al. and the HabiSign approach of Ghosh et al. This latter
1430:
With the increasing availability of samples containing ancient DNA and due to the uncertainty associated with the nature of those samples (ancient DNA damage), a fast tool capable of producing conservative similarity estimates has been made available. According to FALCON's authors, it can use relaxed
1426:
With the advent of fast and inexpensive sequencing instruments, the growth of databases of DNA sequences is now exponential (e.g., the NCBI GenBank database ). Faster and efficient tools are needed to keep pace with the high-throughput sequencing, because the BLAST-based approaches such as MG-RAST or
6981:
Abubucker, Sahar; Segata, Nicola; Goll, Johannes; Schubert, Alyxandria M.; Izard, Jacques; Cantarel, Brandi L.; Rodriguez-Mueller, Beltran; Zucker, Jeremy; Thiagarajan, Mathangi; Henrissat, Bernard; White, Owen; Kelley, Scott T.; Methé, Barbara; Schloss, Patrick D.; Gevers, Dirk; Mitreva, Makedonka;
2017:
shows promise as a sensitive and rapid method to diagnose infection by comparing genetic material found in a patient's sample to databases of all known microscopic human pathogens and thousands of other bacterial, viral, fungal, and parasitic organisms and databases on antimicrobial resistances gene
1972:
While these studies highlight some potentially valuable medical applications, only 31–48.8% of the reads could be aligned to 194 public human gut bacterial genomes and 7.6–21.2% to bacterial genomes available in GenBank which indicates that there is still far more research necessary to capture novel
1829:
Microbial communities produce a vast array of biologically active chemicals that are used in competition and communication. Many of the drugs in use today were originally uncovered in microbes; recent progress in mining the rich genetic resource of non-culturable microbes has led to the discovery of
1461:
as a whole rather than taxonomic groups, and shows that the functional complements are analogous under similar environmental conditions. Consequently, metadata on the environmental context of the metagenomic sample is especially important in comparative analyses, as it provides researchers with the
1860:
of metagenomic data: function-driven screening for an expressed trait, and sequence-driven screening for DNA sequences of interest. Function-driven analysis seeks to identify clones expressing a desired trait or useful activity, followed by biochemical characterization and sequence analysis. This
1374:
associated with metagenomic projects. Metadata includes detailed information about the three-dimensional (including depth, or height) geography and environmental features of the sample, physical data about the sample site, and the methodology of the sampling. This information is necessary both to
1214:
while metagenomic data is usually highly non-redundant. Furthermore, the increased use of second-generation sequencing technologies with short read lengths means that much of future metagenomic data will be error-prone. Taken in combination, these factors make the assembly of metagenomic sequence
1968:
The study demonstrated that two bacterial divisions, Bacteroidetes and
Firmicutes, constitute over 90% of the known phylogenetic categories that dominate distal gut bacteria. Using the relative gene frequencies found within the gut these researchers identified 1,244 metagenomic clusters that are
1964:
Another medical study as part of the MetaHit (Metagenomics of the Human
Intestinal Tract) project consisted of 124 individuals from Denmark and Spain consisting of healthy, overweight, and irritable bowel disease patients. The study attempted to categorize the depth and phylogenetic diversity of
1869:
to screen clones for the sequence of interest. In comparison to cloning-based approaches, using a sequence-only approach further reduces the amount of bench work required. The application of massively parallel sequencing also greatly increases the amount of sequence data generated, which require
1477:
A key goal in comparative metagenomics is to identify microbial group(s) which are responsible for conferring specific characteristics to a given environment. However, due to issues in the sequencing technologies artifacts need to be accounted for like in metagenomeSeq. Others have characterized
957:
Seas. Analysis of the metagenomic data collected during this journey revealed two groups of organisms, one composed of taxa adapted to environmental conditions of 'feast or famine', and a second composed of relatively fewer but more abundantly and widely distributed taxa primarily composed of
1670:
in which plants grow are inhabited by microbial communities, with one gram of soil containing around 10-10 microbial cells which comprise about one gigabase of sequence information. The microbial communities which inhabit soils are some of the most complex known to science, and remain poorly
1965:
gastrointestinal bacteria. Using
Illumina GA sequence data and SOAPdenovo, a de Bruijn graph-based tool specifically designed for assembly short reads, they were able to generate 6.58 million contigs greater than 500 bp for a total contig length of 10.3 Gb and a N50 length of 2.2 kb.
489:
Because of its ability to reveal the previously hidden diversity of microscopic life, metagenomics offers a powerful way of understanding the microbial world that might revolutionize understanding of biology. As the price of DNA sequencing continues to fall, metagenomics now allows
929:(GOS), circumnavigating the globe and collecting metagenomic samples throughout the journey. All of these samples were sequenced using shotgun sequencing, in hopes that new genomes (and therefore new organisms) would be identified. The pilot project, conducted in the
1439:
Comparative analyses between metagenomes can provide additional insight into the function of complex microbial communities and their role in host health. Pairwise or multiple comparisons between metagenomes can be made at the level of sequence composition (comparing
6858:
Qin, Junjie; Li, Ruiqiang; Raes, Jeroen; Arumugam, Manimozhiyan; Burgdorf, Kristoffer
Solvsten; Manichanh, Chaysavanh; Nielsen, Trine; Pons, Nicolas; Levenez, Florence; Yamada, Takuji; Mende, Daniel R.; Li, Junhua; Xu, Junming; Li, Shaochuan; Li, Dongfang (2010).
1466:
study also indicated that differences in tetranucleotide usage patterns can be used to identify genes (or metagenomic reads) originating from specific habitats. Additionally some methods as TriageTools or
Compareads detect similar reads between two read sets. The
1448:
and other phylogenetic marker genes, or—in the case of low-diversity communities—by genome reconstruction from the metagenomic dataset. Functional comparisons between metagenomes may be made by comparing sequences against reference databases such as
1358:, use read coverage landscape of individual reference genomes to minimize false-positive hits and get reliable relative abundances. In composition based binning, methods use intrinsic features of the sequence, such as oligonucleotide frequencies or
1183:
gene catalog identified 3.3 million genes assembled from 567.7 gigabases of sequence data. Collecting, curating, and extracting useful biological information from datasets of this size represent significant computational challenges for researchers.
841:
to explore the diversity of ribosomal RNA sequences. The insights gained from these breakthrough studies led Pace to propose the idea of cloning DNA directly from environmental samples as early as 1985. This led to the first report of isolating and
1075:
An advantage to high throughput sequencing is that this technique does not require cloning the DNA before sequencing, removing one of the main biases and bottlenecks in environmental sampling. The first metagenomic studies conducted using
1925:
and for cleaning up contaminated environments. Increased understanding of how microbial communities cope with pollutants improves assessments of the potential of contaminated sites to recover from pollution and increases the chances of
1894:
DNA sequencing can also be used more broadly to identify species present in a body of water, debris filtered from the air, sample of dirt, or animal's faeces, and even detect diet items from blood meals. This can establish the range of
1949:, but their composition and the mechanism by which they do so remains mysterious. Metagenomic sequencing is being used to characterize the microbial communities from 15–18 body sites from at least 250 individuals. This is part of the
2000:
In animals, metagenomics can be used to profile their gut microbiomes and enable detection of antibiotic-resistant bacteria. This can have implications in monitoring the spread of diseases from wildlife to farmed animals and humans.
7730:
1383:
Several tools have been developed to integrate metadata and sequence data, allowing downstream comparative analyses of different datasets using a number of ecological indices. In 2007, Folker Meyer and Robert
Edwards and a team at
2531:
Healy FG, Ray RM, Aldrich HC, Wilkie AC, Ingram LO, Shanmugam KT (1995). "Direct isolation of functional genes encoding cellulases from the microbial consortia in a thermophilic, anaerobic digester maintained on lignocellulose".
1219:
that make assembly especially difficult because of the difference in the relative abundance of species present in the sample. Misassemblies can also involve the combination of sequences from more than one species into chimeric
1379:
and to enable downstream analysis. Because of its importance, metadata and collaborative data review and curation require standardized data formats located in specialized databases, such as the
Genomes OnLine Database (GOLD).
522:, and Sean F. Brady, and first appeared in publication in 1998. The term metagenome referenced the idea that a collection of genes sequenced from the environment could be analyzed in a way analogous to the study of a single
1303:
prediction is that it enables the detection of coding regions that lack homologs in the sequence databases; however, it is most accurate when there are large regions of contiguous genomic DNA available for comparison.
1798:. Furthermore, knowledge of how these microbial communities function is required to control them, and metagenomics is a key tool in their understanding. Metagenomic approaches allow comparative analyses between
1988:
degradation in the gut, as well as phosphate and amino acid transport linked to host phenotype (vaginal pH) in the posterior fornix. The HMP has brought to light the utility of metagenomics in diagnostics and
1560:
Metagenomics allows researchers to access the functional and metabolic diversity of microbial communities, but it cannot show which of these processes are active. The extraction and analysis of metagenomic
1891:
This is because the bacteria that are expelled simultaneously with the defecations are adept at breaking down the nutrients in the faeces into a bioavailable form that can be taken up into the food chain.
866:
continued in the field and has published work that has largely laid the groundwork for environmental phylogenies based on signature 16S sequences, beginning with his group's construction of libraries from
5902:
1107:(Hi-C), which measures the proximity of any two DNA sequences within the same cell, to guide microbial genome assembly. Long read sequencing technologies, including PacBio RSII and PacBio Sequel by
3062:
Béjà O, Suzuki MT, Koonin EV, Aravind L, Hadd A, Nguyen LP, et al. (October 2000). "Construction and analysis of bacterial artificial chromosome libraries from a marine microbial assemblage".
2686:
Tyson GW, Chapman J, Hugenholtz P, Allen EE, Ram RJ, Richardson PM, et al. (March 2004). "Community structure and metabolism through reconstruction of microbial genomes from the environment".
1051:, refinements of DNA amplification, and the proliferation of computational power have greatly aided the analysis of DNA sequences recovered from environmental samples, allowing the adaptation of
1400:(IMG/M) system also provides a collection of tools for functional analysis of microbial communities based on their metagenome sequence, based upon reference isolate genomes included from the
6335:
1192:
The first step of metagenomic data analysis requires the execution of certain pre-filtering steps, including the removal of redundant, low-quality sequences and sequences of probable
4393:
Sunagawa S, Mende DR, Zeller G, Izquierdo-Carrasco F, Berger SA, Kultima JR, et al. (December 2013). "Metagenomic species profiling using universal phylogenetic marker genes".
1171:
The data generated by metagenomics experiments are both enormous and inherently noisy, containing fragmented data representing as many as 10,000 species. The sequencing of the cow
6732:"A two-step metagenomics approach for the identification and mitochondrial DNA contig assembly of vertebrate prey from the blood meals of common vampire bats (Desmodus rotundus)"
2009:
Differentiating between infectious and non-infectious illness, and identifying the underlying etiology of infection, can be challenging. For example, more than half of cases of
1167:
Schematic representation of the main steps necessary for the analysis of whole metagenome shotgun sequencing-derived data. The software related to each step is shown in italics.
1984:
project. The metagenomic analysis revealed variations in niche specific abundance among 168 functional modules and 196 metabolic pathways within the microbiome. These included
1457:, and tabulating the abundance by category and evaluating any differences for statistical significance. This gene-centric approach emphasizes the functional complement of the
1196:
origin (especially in metagenomes of human origin). The methods available for the removal of contaminating eukaryotic genomic DNA sequences include Eu-Detect and DeConseq.
826:
species in a sample. Much of the interest in metagenomics comes from these discoveries that showed that the vast majority of microorganisms had previously gone unnoticed.
1291:, uses intrinsic features of the sequence to predict coding regions based upon gene training sets from related organisms. This is the approach taken by programs such as
3459:
Hess M, Sczyrba A, Egan R, Kim TW, Chokhawala H, Schroth G, et al. (January 2011). "Metagenomic discovery of biomass-degrading genes and genomes from cow rumen".
4952:
Pratas D, Pinho AJ, Silva RM, Rodrigues JM, Hosseini M, Caetano T, Ferreira PJ (February 2018). "FALCON: a method to infer metagenomic composition of ancient DNA".
3835:
Mohammed MH, Chadaram S, Komanduri D, Ghosh TS, Mande SS (September 2011). "Eu-Detect: an algorithm for detecting eukaryotic sequences in metagenomic data sets".
2909:
Poinar HN, Schwarz C, Qi J, Shapiro B, Macphee RD, Buigues B, et al. (January 2006). "Metagenomics to paleogenomics: large-scale sequencing of mammoth DNA".
5910:
2791:
Venter JC, Remington K, Heidelberg JF, Halpern AL, Rusch D, Eisen JA, et al. (April 2004). "Environmental genome shotgun sequencing of the
Sargasso Sea".
854:
false positives and supported the existence of a complex community of unexplored species. Although this methodology was limited to exploring highly conserved,
6730:
Chua, Physilia Y. S.; Carøe, Christian; Crampton-Platt, Alex; Reyes-Avila, Claudia S.; Jones, Gareth; Streicker, Daniel G.; Bohmann, Kristine (4 July 2022).
1346:
are methods based on unique clade-specific markers for estimating organismal relative abundances with improved computational performances. Other tools, like
5470:
Leininger S, Urich T, Schloter M, Schwark L, Qi J, Nicol GW, et al. (August 2006). "Archaea predominate among ammonia-oxidizing prokaryotes in soils".
7725:
1444:
or genome size), taxonomic diversity, or functional complement. Comparisons of population structure and phylogenetic diversity can be made on the basis of
2030:(blood-feeding) insects such as mosquitoes and ticks. Metagenomics is routinely used by public health officials and organisations for the surveillance of
417:) to deduce the individual genomes or parts of genomes that constitute the original environmental sample. This information can then be used to study the
352:
1055:
to metagenomic samples (known also as whole metagenome shotgun or WMGS sequencing). The approach, used to sequence many cultured microorganisms and the
6498:"Culture-independent discovery of the malacidins as calcium-dependent antibiotics with activity against multidrug-resistant Gram-positive pathogens"
886:(see below) to show that 200 liters of seawater contains over 5000 different viruses. Subsequent studies showed that there are more than a thousand
818:, indicating that there are numerous non-isolated organisms. These surveys of ribosomal RNA genes taken directly from the environment revealed that
534:) defined metagenomics as "the application of modern genomics technique without the need for isolation and lab cultivation of individual species".
774:
610:
6366:
1330:
are used to rapidly search for phylogenetic markers or otherwise similar sequences in existing public databases. This approach is implemented in
2446:
Pace NR, Stahl DA, Lane DJ, Olsen GJ (1986). "The Analysis of Natural Microbial Populations by Ribosomal RNA Sequences". In Marshall KC (ed.).
2577:"Characterization of uncultivated prokaryotes: isolation and analysis of a 40-kilobase-pair genome fragment from a planktonic marine archaeon"
1354:
is possible to profile species without a reference genome, improving the estimation of microbial community diversity. Recent methods, such as
7767:
6839:
6788:
6315:
6029:
3654:
2463:
2219:
641:
5986:
1613:
Metagenomic sequencing is particularly useful in the study of viral communities. As viruses lack a shared universal phylogenetic marker (as
1886:
Metagenomics allows the study of microbial communities like those present in this stream receiving acid drainage from surface coal mining.
1599:
to measure whole-genome expression and quantification of a microbial community, first employed in analysis of ammonia oxidation in soils.
1638:
Metagenomics has the potential to advance knowledge in a wide variety of fields. It can also be applied to solve practical challenges in
795:. However, early metagenomic studies revealed that there are probably large groups of microorganisms in many environments that cannot be
7882:
1397:
7452:
899:
728:
531:
6596:"High nutrient transport and cycling potential revealed in the microbial metagenome of Australian sea lion (Neophoca cinerea) faeces"
5826:
Kerepesi C, Grolmusz V (June 2017). "The "Giant Virus Finder" discovers an abundance of giant viruses in the Antarctic dry valleys".
1786:
with higher productivity and lower cost. Metagenomic approaches to the analysis of complex microbial communities allow the targeted
1269:
use two approaches in the annotation of coding regions in the assembled contigs. The first approach is to identify genes based upon
1957:, to understand the changes in the human microbiome that can be correlated with human health, and to develop new technological and
6679:
Chua, Physilia Y. S.; Crampton-Platt, Alex; Lammers, Youri; Alsos, Inger G.; Boessenkool, Sanne; Bohmann, Kristine (25 May 2021).
7887:
926:
723:
718:
7799:
7745:
2014:
1370:
The massive amount of exponentially growing sequence data is a daunting challenge that is complicated by the complexity of the
1104:
1028:
942:
846:
bulk DNA from an environmental sample, published by Pace and colleagues in 1991 while Pace was in the Department of Biology at
898:. Essentially all of the viruses in these studies were new species. In 2004, Gene Tyson, Jill Banfield, and colleagues at the
345:
6047:"Pivotal roles of phyllosphere microorganisms at the interface between plant functioning and atmospheric trace gas dynamics"
7773:
2026:
Metagenomics has been an invaluable tool to help characterise the diversity and ecology of pathogens that are vectored by
1210:
DNA sequence data from genomic and metagenomic projects are essentially the same, but genomic sequence data offers higher
1140:
about quality assessment: on assembly (N50, MetaQUAST), on genome (universal single-copy marker genes – CheckM and BUSCO).
6653:
4649:"The metagenomics RAST server - a public resource for the automatic phylogenetic and functional analysis of metagenomes"
1596:
1549:
1112:
1085:
6984:"PLOS Computational Biology: Metabolic Reconstruction for Metagenomic Data and Its Application to the Human Microbiome"
997:
7689:
7417:
3165:
Rodrigue S, Materna AC, Timberlake SC, Blackburn MC, Malmstrom RR, Alm EJ, Chisholm SW (July 2010). Gilbert JA (ed.).
1779:
1385:
712:
7263:"Uncovering the Worldwide Diversity and Evolution of the Virome of the Mosquitoes Aedes aegypti and Aedes albopictus"
6206:
Suen G, Scott JJ, Aylward FO, Adams SM, Tringe SG, Pinto-Tomás AA, et al. (September 2010). Sonnenburg J (ed.).
5880:
1322:
provide the "who". In order to connect community composition and function in metagenomes, sequences must be binned.
7825:
6149:"Comparative and joint analysis of two metagenomic datasets from a biogas fermenter obtained by 454-pyrosequencing"
1866:
1326:
is the process of associating a particular sequence with an organism. In similarity-based binning, methods such as
1032:
986:
698:
114:
6805:
4600:"The Genomes OnLine Database (GOLD) v.4: status of genomic and metagenomic projects and their associated metadata"
3680:"Metagenomics: tools and insights for analyzing next-generation sequencing data derived from biodiversity studies"
502:
directed sequencing to get largely unbiased samples of all genes from all the members of the sampled communities.
7779:
5521:
Paez-Espino D, Eloe-Fadrosh EA, Pavlopoulos GA, Thomas AD, Huntemann M, Mikhailova N, et al. (August 2016).
5141:"HabiSign: a novel approach for comparison of metagenomes and rapid identification of habitat-specific sequences"
851:
838:
767:
682:
499:
338:
5627:"IMG/VR v.2.0: an integrated data management and analysis system for cultivated and environmental viral genomes"
7735:
7580:
7512:
6547:"Toward molecular trait-based ecology through integration of biogeochemical, geographical and metagenomic data"
5288:"Community-analyzer: a platform for visualizing and comparing microbial community structure across microbiomes"
1977:
1950:
132:
6020:
Charles T (2010). "The Potential for Investigation of Plant-microbe Interactions Using Metagenomics Methods".
5924:
Vogel TM, Simonet P, Jansson JK, Hirsch PR, Tiedje JM, Van Elsas JD, Bailey MJ, Nalin R, Philippot L (2009).
7872:
7720:
7592:
3407:"Metagenomic approaches in microbial ecology: an update on whole-genome and marker gene sequencing analyses"
2288:"Molecular biological access to the chemistry of unknown soil microbes: a new frontier for natural products"
1990:
1216:
819:
796:
587:
475:
6779:
George I, Stenuit B, Agathos SN (2010). "Application of Metagenomics to Bioremediation". In Marco D (ed.).
6147:
Jaenicke S, Ander C, Bekel T, Bisdorf R, Dröge M, Gartemann KH, et al. (January 2011). Aziz RK (ed.).
37:
7761:
7677:
7480:
7445:
6447:"Isolation of xylose isomerases by sequence- and function-based screening from a soil metagenomic library"
4903:"CLARK: fast and accurate classification of metagenomic and genomic sequences using discriminative k-mers"
2808:
2237:"Environmental shotgun sequencing: its potential and challenges for studying the hidden world of microbes"
2211:
2043:
1882:
1536:
and proteomics) in the quest to determine how metabolites are transferred and transformed by a community.
1323:
903:
760:
747:
482:
gene) to produce a profile of diversity in a natural sample. Such work revealed that the vast majority of
6830:
Nelson KE and White BA (2010). "Metagenomics and Its Applications to the Study of the Human Microbiome".
1830:
new genes, enzymes, and natural products. The application of metagenomics has allowed the development of
1503:), during which the waste products of some organisms are metabolites for others. In one such system, the
1362:. Once sequences are binned, it is possible to carry out comparative analysis of diversity and richness.
7867:
7740:
7694:
1994:
1942:
1389:
1327:
1278:
1247:, have been optimized for the shorter reads produced by second-generation sequencing through the use of
966:
910:
system. This effort resulted in the complete, or nearly complete, genomes for a handful of bacteria and
305:
285:
250:
162:
157:
3997:"MetaVelvet: an extension of Velvet assembler to de novo metagenome assembly from short sequence reads"
2960:
Edwards RA, Rodriguez-Brito B, Wegley L, Haynes M, Breitbart M, Peterson DM, et al. (March 2006).
5675:
1115:, is another choice to get long shotgun sequencing reads that should make ease in assembling process.
7500:
7485:
7325:
7168:
6995:
6937:
6872:
6607:
6160:
5985:
Committee on Metagenomics: Challenges and Functional Applications, National Research Council (2007).
5534:
5479:
5340:
5103:
5046:
4953:
4452:
4256:
3891:
3740:
3635:
Committee on Metagenomics: Challenges and Functional Applications, National Research Council (2007).
3523:
3468:
3312:
3178:
3071:
2918:
2865:
2800:
2695:
2637:
2400:
2341:
2108:
1814:
1799:
1756:
1751:. This process is dependent upon microbial consortia (association) that transform the cellulose into
1243:
but nevertheless produce good results when assembling metagenomic data sets. Other programs, such as
1093:
1056:
922:
597:
592:
3678:
Oulas A, Pavloudi C, Polymenakou P, Pavlopoulos GA, Papanikolaou N, Kotoulas G, et al. (2015).
2813:
365:
7710:
7684:
7542:
7529:
7490:
4801:
Benson DA, Cavanaugh M, Clark K, Karsch-Mizrachi I, Lipman DJ, Ostell J, Sayers EW (January 2013).
3727:
Mende DR, Waller AS, Sunagawa S, Järvelin AI, Chan MM, Arumugam M, et al. (23 February 2012).
1843:
1831:
1795:
1672:
1555:
1512:
1266:
1163:
1108:
668:
602:
433:
280:
260:
225:
195:
152:
146:
137:
109:
5188:"TriageTools: tools for partitioning and prioritizing analysis of high-throughput sequencing data"
2013:
remain undiagnosed, despite extensive testing using state-of-the-art clinical laboratory methods.
7664:
7475:
7078:
6761:
5995:
5861:
5835:
5808:
5782:
5706:
5558:
5503:
4418:
3880:"Fast identification and removal of sequence contamination from genomic and metagenomic datasets"
3860:
3492:
3249:
3095:
2942:
2834:
2719:
2557:
1900:
1862:
1748:
1623:
1608:
1467:
1270:
1089:
1064:
1052:
907:
883:
847:
807:
693:
677:
657:
615:
495:
406:
275:
270:
245:
167:
2159:"Impact of culture-independent studies on the emerging phylogenetic view of bacterial diversity"
1710:
practices which improve crop health by harnessing the relationship between microbes and plants.
5327:
Werner JJ, Knights D, Garcia ML, Scalfone NB, Smith S, Yarasheski K, et al. (March 2011).
4095:"Species-level deconvolution of metagenome assemblies with Hi-C-based contact probability maps"
2624:
Breitbart M, Salamon P, Andresen B, Mahaffy JM, Segall AM, Mead D, et al. (October 2002).
7877:
7715:
7524:
7438:
7412:
7392:
7351:
7294:
7243:
7194:
7137:
7119:
7070:
7062:
7023:
6963:
6906:
6888:
6835:
6784:
6753:
6712:
6635:
6576:
6527:
6478:
6427:
6358:
6311:
6288:
6239:
6188:
6129:
6078:
6025:
5853:
5800:
5755:
5698:
5656:
5607:
5550:
5495:
5452:
5417:
5368:
5309:
5268:
5217:
5168:
5121:
5072:
5004:
4934:
4883:
4832:
4783:
4729:
4698:
Markowitz VM, Chen IM, Chu K, Szeto E, Palaniappan K, Grechkin Y, et al. (January 2012).
4680:
4629:
4580:
4529:
4478:
4410:
4375:
4326:
4274:
4225:
4176:
4124:
4075:
4026:
3977:
3919:
3852:
3817:
3768:
3709:
3660:
3650:
3604:
3549:
3484:
3438:
3387:
3338:
3299:
Stewart RD, Auffret MD, Warr A, Wiser AH, Press MO, Langford KW, et al. (February 2018).
3241:
3206:
3147:
3087:
3044:
2993:
2934:
2883:
2826:
2773:
2711:
2665:
2606:
2549:
2513:
2459:
2428:
2369:
2309:
2268:
2215:
2188:
2136:
2058:
1993:. Thus metagenomics is a powerful tool to address many of the pressing issues in the field of
1985:
1680:
1676:
1618:
1614:
1582:
1445:
1313:
1274:
1205:
1143:
1097:
1060:
1036:
1024:
1020:
1016:
978:
950:
830:
707:
635:
558:
515:
494:
to be investigated at a much greater scale and detail than before. Recent studies use either "
491:
479:
464:
418:
410:
398:
325:
210:
89:
5576:
Paez-Espino D, Chen IA, Palaniappan K, Ratner A, Chu K, Szeto E, et al. (January 2017).
4439:
Milanese A, Mende DR, Paoli L, Salazar G, Ruscheweyh HJ, Cuenca M, et al. (March 2019).
7639:
7634:
7382:
7341:
7333:
7284:
7274:
7233:
7225:
7184:
7176:
7127:
7109:
7054:
7013:
7003:
6953:
6945:
6896:
6880:
6743:
6702:
6692:
6625:
6615:
6566:
6558:
6517:
6509:
6468:
6458:
6417:
6409:
6350:
6278:
6270:
6229:
6219:
6178:
6168:
6119:
6109:
6068:
6058:
5937:
5845:
5792:
5745:
5737:
5690:
5646:
5638:
5625:
Paez-Espino D, Roux S, Chen IA, Palaniappan K, Ratner A, Chu K, et al. (January 2019).
5597:
5589:
5542:
5487:
5444:
5407:
5399:
5358:
5348:
5299:
5258:
5248:
5207:
5199:
5158:
5148:
5111:
5062:
5054:
4994:
4986:
4924:
4914:
4873:
4863:
4822:
4814:
4773:
4763:
4719:
4711:
4670:
4660:
4619:
4611:
4570:
4560:
4519:
4509:
4468:
4460:
4402:
4365:
4357:
4316:
4308:
4264:
4215:
4207:
4166:
4158:
4114:
4106:
4065:
4057:
4016:
4008:
3967:
3959:
3909:
3899:
3844:
3807:
3799:
3758:
3748:
3699:
3691:
3642:
3594:
3586:
3539:
3531:
3476:
3428:
3418:
3377:
3369:
3328:
3320:
3279:
3233:
3196:
3186:
3137:
3129:
3079:
3034:
3024:
2983:
2973:
2926:
2873:
2818:
2763:
2753:
2703:
2655:
2645:
2596:
2588:
2541:
2503:
2495:
2451:
2418:
2408:
2359:
2349:
2299:
2258:
2248:
2178:
2170:
2126:
2116:
1981:
1954:
1896:
1850:
1847:
1684:
1411:
One of the first standalone tools for analysing high-throughput metagenome shotgun data was
1359:
1244:
472:
217:
4598:
Pagani I, Liolios K, Jansson J, Chen IM, Smirnova T, Nosrat B, et al. (January 2012).
2852:
Yooseph S, Nealson KH, Rusch DB, McCrow JP, Dupont CL, Kim M, et al. (November 2010).
7851:
7654:
7644:
7629:
7565:
6496:
Hover BM, Kim SH, Katz M, Charlop-Powers Z, Owen JG, Ternei MA, et al. (April 2018).
4647:
Meyer F, Paarmann D, D'Souza M, Olson R, Glass EM, Kubal M, et al. (September 2008).
1927:
1574:
1570:
1260:
1248:
891:
5676:"Nontargeted virus sequence discovery pipeline and virus clustering for metagenomic data"
5329:"Bacterial community structures are unique and resilient in full-scale bioenergy systems"
4750:
Mitra S, Rupek P, Richter DC, Urich T, Gilbert JA, Meyer F, et al. (February 2011).
1591:
metatranscriptomic studies of microbial communities to date. While originally limited to
1215:
reads into genomes difficult and unreliable. Misassemblies are caused by the presence of
7329:
7172:
6999:
6941:
6876:
6611:
6164:
5538:
5483:
5344:
5107:
5050:
4975:"Comparative metagenomics revealed commonly enriched gene sets in human gut microbiomes"
4456:
4260:
3895:
3744:
3527:
3472:
3316:
3182:
3075:
2922:
2869:
2804:
2699:
2641:
2404:
2345:
2112:
1142:
Please expand the section to include this information. Further details may exist on the
7839:
7811:
7649:
7552:
7495:
7346:
7313:
7289:
7262:
7238:
7213:
7189:
7156:
7132:
7097:
7018:
6983:
6958:
6925:
6901:
6860:
6707:
6680:
6630:
6595:
6571:
6546:
6522:
6497:
6473:
6446:
6422:
6397:
6283:
6258:
6234:
6207:
6183:
6148:
6124:
6097:
6073:
6046:
5750:
5725:
5651:
5626:
5602:
5577:
5412:
5387:
5363:
5328:
5263:
5236:
5212:
5187:
5163:
5140:
5067:
5034:
4999:
4974:
4929:
4902:
4878:
4851:
4827:
4802:
4778:
4751:
4724:
4699:
4675:
4648:
4624:
4599:
4575:
4548:
4524:
4498:"Accurate and fast estimation of taxonomic profiles from metagenomic shotgun sequences"
4497:
4473:
4440:
4370:
4345:
4321:
4296:
4220:
4195:
4171:
4146:
4119:
4094:
4070:
4045:
4021:
3996:
3972:
3947:
3914:
3879:
3812:
3787:
3763:
3728:
3704:
3679:
3599:
3574:
3544:
3511:
3433:
3406:
3382:
3357:
3333:
3300:
3201:
3166:
3142:
3117:
3039:
3012:
2988:
2961:
2479:
2364:
2329:
2263:
2236:
2131:
2096:
2053:
1958:
1931:
1912:
1857:
1835:
1818:
1787:
1651:
1592:
1228:
1081:
1077:
1048:
1006:
974:
970:
969:
and colleagues published the first sequences of an environmental sample generated with
895:
868:
834:
390:
378:
265:
190:
7314:"Sensitivity and specificity of metatranscriptomics as an arbovirus surveillance tool"
6354:
4973:
Kurokawa K, Itoh T, Kuwahara T, Oshima K, Toh H, Toyoda A, et al. (August 2007).
4344:
Segata N, Waldron L, Ballarini A, Narasimhan V, Jousson O, Huttenhower C (June 2012).
2768:
2741:
2660:
2625:
2601:
2576:
2508:
2483:
2423:
2388:
2304:
2287:
2183:
2158:
7861:
7624:
7570:
7534:
7082:
7042:
6924:
Qin J, Li R, Raes J, Arumugam M, Burgdorf KS, Manichanh C, et al. (March 2010).
6765:
5116:
5091:
3510:
Qin J, Li R, Raes J, Arumugam M, Burgdorf KS, Manichanh C, et al. (March 2010).
3224:
Schuster SC (January 2008). "Next-generation sequencing transforms today's biology".
3083:
2499:
2484:"Analysis of a marine picoplankton community by 16S rRNA gene cloning and sequencing"
2174:
2063:
2027:
1545:
1376:
1211:
982:
887:
879:
875:
863:
855:
569:
565:
550:
511:
7155:
Zakrzewski M, Rašić G, Darbro J, Krause L, Poo YS, Filipović I, et al. (2018).
5812:
4346:"Metagenomic microbial community profiling using unique clade-specific marker genes"
3864:
3803:
3729:"Assessment of metagenomic assembly using simulated next generation sequencing data"
3496:
2946:
2758:
2561:
1350:
and MetaPhyler, use universal marker genes to profile prokaryotic species. With the
7614:
7575:
7387:
7370:
5903:"Towards "Tera-Terra": Terabase Sequencing of Terrestrial Metagenomes Print E-mail"
5865:
5710:
5562:
5507:
4422:
3253:
3116:
Segata N, Boernigen D, Tickle TL, Morgan XC, Garrett WS, Huttenhower C (May 2013).
3099:
2838:
2723:
2010:
1839:
1450:
1335:
1319:
930:
918:
527:
483:
460:
381:
directly from samples taken from the environment (e.g. soil, sea water, human gut,
255:
7279:
6594:
Lavery TJ, Roudnew B, Seymour J, Mitchell JG, Jeffries T (2012). Steinke D (ed.).
6413:
4700:"IMG/M: the integrated metagenome data management and comparative analysis system"
2592:
1431:
thresholds and edit distances without affecting the memory and speed performance.
7008:
6620:
6224:
6173:
5448:
5435:
Klitgord N, Segrè D (August 2011). "Ecosystems biology of microbial metabolism".
5403:
5253:
3904:
3753:
3358:"Metagenomics and Bioinformatics in Microbial Ecology: Current Status and Beyond"
3191:
2354:
2253:
2121:
7587:
7519:
5304:
5287:
5153:
4768:
3301:"Assembly of 913 microbial genomes from metagenomic sequencing of the cow rumen"
2455:
1772:
1744:
1707:
1688:
1647:
1643:
1533:
1519:) working together in order to turn raw resources into fully metabolized waste (
1516:
843:
7834:
7337:
7180:
7058:
5522:
5333:
Proceedings of the National Academy of Sciences of the United States of America
4752:"Functional analysis of metagenomes and metatranscriptomes using SEED and KEGG"
4514:
4464:
3324:
2630:
Proceedings of the National Academy of Sciences of the United States of America
2393:
Proceedings of the National Academy of Sciences of the United States of America
1339:
7672:
7619:
7609:
7604:
7114:
6513:
6274:
5849:
5796:
5741:
4919:
3848:
3638:
The New Science of Metagenomics: Revealing the Secrets of Our Microbial Planet
2389:"Rapid determination of 16S ribosomal RNA sequences for phylogenetic analyses"
1768:
1528:
1524:
1504:
1496:
1462:
ability to study the effect of habitat upon community structure and function.
1441:
1405:
1392:
released the Metagenomics Rapid Annotation using Subsystem Technology server (
1193:
1180:
1084:. Three other technologies commonly applied to environmental sampling are the
946:
788:
519:
437:
185:
99:
79:
54:
7123:
7066:
6892:
6757:
6063:
2330:"Bioinformatics for whole-genome shotgun sequencing of microbial communities"
1179:, or 279 billion base pairs of nucleotide sequence data, while the human gut
7731:
Matrix-assisted laser desorption ionization-time of flight mass spectrometer
7599:
6926:"A human gut microbial gene catalogue established by metagenomic sequencing"
6861:"A human gut microbial gene catalogue established by metagenomic sequencing"
6697:
5578:"IMG/VR: a database of cultured and uncultured DNA Viruses and retroviruses"
5353:
4990:
4868:
4665:
4441:"Microbial abundance, activity and population genomic profiling with mOTUs2"
3946:
Kunin V, Copeland A, Lapidus A, Mavromatis K, Hugenholtz P (December 2008).
3512:"A human gut microbial gene catalogue established by metagenomic sequencing"
3480:
2930:
2822:
2413:
2031:
1922:
1918:
1871:
1810:
1764:
1736:
1703:
1577:
profiles of complex communities. Because of the technical difficulties (the
1508:
1500:
1401:
1287:
1227:
There are several assembly programs, most of which can use information from
1096:
system. These techniques for sequencing DNA generate shorter fragments than
1012:
954:
800:
142:
7396:
7355:
7298:
7247:
7214:"Targeted Metagenomics Offers Insights into Potential Tick-Borne Pathogens"
7198:
7141:
7074:
7027:
6967:
6910:
6716:
6639:
6580:
6531:
6482:
6431:
6362:
6292:
6243:
6208:"An insect herbivore microbiome with high plant biomass-degrading capacity"
6192:
6133:
6114:
6082:
5857:
5804:
5759:
5702:
5694:
5660:
5611:
5554:
5499:
5456:
5421:
5372:
5313:
5272:
5221:
5172:
5125:
5076:
5008:
4938:
4887:
4836:
4787:
4733:
4684:
4633:
4584:
4533:
4482:
4414:
4379:
4330:
4278:
4229:
4180:
4128:
4079:
4046:"Velvet: algorithms for de novo short read assembly using de Bruijn graphs"
4030:
3981:
3923:
3856:
3821:
3772:
3713:
3664:
3608:
3553:
3488:
3442:
3391:
3342:
3245:
3210:
3151:
3091:
3048:
2997:
2978:
2938:
2887:
2854:"Genomic and functional adaptation in surface ocean planktonic prokaryotes"
2830:
2777:
2715:
2669:
2650:
2373:
2272:
2140:
1128:
6731:
6463:
6306:
Wong D (2010). "Applications of Metagenomics for Industrial Bioproducts".
5773:
Kerepesi C, Grolmusz V (March 2016). "Giant viruses of the Kutch Desert".
5642:
5593:
4818:
4615:
4269:
4244:
4162:
4110:
4061:
3963:
3423:
3373:
3284:
3267:
3029:
2610:
2553:
2517:
2432:
2313:
2192:
7461:
7229:
7157:"Mapping the virome in wild-caught Aedes aegypti from Cairns and Bangkok"
6748:
5203:
5058:
4715:
4211:
4145:
Huson DH, Mitra S, Ruscheweyh HJ, Weber N, Schuster SC (September 2011).
4012:
1639:
1371:
1292:
1176:
959:
938:
468:
429:
201:
84:
74:
29:
7425:
The “Critical Assessment of Metagenome Interpretation” (CAMI) initiative
6949:
6884:
6098:"Bioprospecting metagenomes: glycosyl hydrolases for converting biomass"
5942:
5925:
5546:
5491:
4549:"SLIMM: species level identification of microorganisms from metagenomes"
3636:
3535:
3133:
2878:
2853:
2707:
2286:
Handelsman J, Rondon MR, Brady SF, Clardy J, Goodman RM (October 1998).
890:
in human stool and possibly a million different viruses per kilogram of
7560:
6562:
6398:"Size Does Matter: Application-driven Approaches for Soil Metagenomics"
4565:
4406:
4361:
4312:
3695:
3590:
2545:
2387:
Lane DJ, Pace B, Olsen GJ, Stahl DA, Sogin ML, Pace NR (October 1985).
1791:
1783:
1760:
1732:
1724:
1719:
1655:
1587:
1520:
1393:
1343:
1296:
1231:
in order to improve the accuracy of assemblies. Some programs, such as
981:. Another early paper in this area appeared in 2006 by Robert Edwards,
934:
911:
823:
815:
478:, early environmental gene sequencing cloned specific genes (often the
421:
and functional potential of the microbial community of the environment.
5674:
Paez-Espino D, Pavlopoulos GA, Ivanova NN, Kyrpides NC (August 2017).
3237:
1478:
inter-microbial interactions between the resident microbial groups. A
1470:
they apply on reads is based on a number of identical words of length
6096:
Li LL, McCorkle SR, Monchy S, Taghavi S, van der Lelie D (May 2009).
2048:
1946:
1807:
1803:
1240:
1236:
1221:
523:
94:
69:
6259:"Achievements and new knowledge unraveled by metagenomic approaches"
814:
sequences have been found which do not belong to any known cultured
810:
within a species, and generally different between species. Many 16S
5988:
Understanding Our Microbial Planet: The New Science of Metagenomics
5926:"TerraGenome: A consortium for the sequencing of a soil metagenome"
5840:
5726:"New dimensions of the virus world discovered through metagenomics"
4958:
3646:
3575:"Differential abundance analysis for microbial marker-gene surveys"
2962:"Using pyrosequencing to shed light on deep mine microbial ecology"
2095:
Wooley JC, Godzik A, Friedberg I (February 2010). Bourne PE (ed.).
1416:
7371:"Metagenomic arbovirus detection using MinION nanopore sequencing"
5787:
5235:
Maillet N, Lemaitre C, Chikhi R, Lavenier D, Peterlongo P (2012).
1881:
1752:
1740:
1695:
1627:
1523:). Using comparative gene studies and expression experiments with
1507:
bioreactor, functional stability requires the presence of several
1412:
1331:
1282:
1232:
1172:
859:
364:
5724:
Kristensen DM, Mushegian AR, Dolja VV, Koonin EV (January 2010).
5139:
Ghosh TS, Mohammed MH, Rajasingh H, Chadaram S, Mande SS (2011).
2575:
Stein JL, Marsh TL, Wu KY, Shizuya H, DeLong EF (February 1996).
1917:
Metagenomics can improve strategies for monitoring the impact of
1355:
799:
and thus cannot be sequenced. These early studies focused on 16S
7369:
Batovska J, Lynch SE, Rodoni BC, Sawbridge TI, Cogan NO (2017).
7041:
Chua, Physilia Ying Shi; Rasmussen, Jacob Agerbo (11 May 2022).
1728:
1699:
1691:
1667:
1578:
1562:
1454:
1420:
811:
7434:
6681:"Metagenomics: A viable tool for reconstructing herbivore diet"
7312:
Batovska J, Mee PT, Lynch SE, Sawbridge TI, Rodoni BC (2019).
5957:
5092:"Metagenomic signatures of 86 microbial and viral metagenomes"
4852:"A comparative evaluation of sequence classification programs"
4147:"Integrative analysis of environmental sequences using MEGAN4"
1495:
In many bacterial communities, natural or engineered (such as
1479:
1281:
searches. This type of approach is implemented in the program
1122:
803:
792:
370:
64:
59:
6545:
Raes J, Letunic I, Yamada T, Jensen LJ, Bork P (March 2011).
3995:
Namiki T, Hachiya T, Tanaka H, Sakakibara Y (November 2012).
945:, and completed a two-year expedition in 2006 to explore the
409:. These short sequences can then be put together again using
7424:
4547:
Dadi TH, Renard BY, Wieler LH, Semmler T, Reinert K (2017).
1794:
with industrial applications in biofuel production, such as
7430:
1318:
Gene annotations provide the "what", while measurements of
1059:, randomly shears DNA, sequences many short sequences, and
3118:"Computational meta'omics for microbial community studies"
2626:"Genomic analysis of uncultured marine viral communities"
1595:
technology, metatranscriptomics studies have made use of
1499:), there is significant division of labor in metabolism (
1351:
1347:
4901:
Ounit R, Wanamaker S, Close TJ, Lonardi S (March 2015).
4196:"Ab initio gene identification in metagenomic sequences"
4093:
Burton JN, Liachko I, Dunham MJ, Shendure J (May 2014).
3788:"Filtering duplicate reads from 454 pyrosequencing data"
791:
begins with a culture of identical cells as a source of
3786:
Balzer S, Malde K, Grohme MA, Jonassen I (April 2013).
3573:
Paulson JN, Stine OC, Bravo HC, Pop M (December 2013).
3013:"Metagenomics - a guide from sampling to data analysis"
1239:
Assembler, were designed to be used to assemble single
914:
that had previously resisted attempts to culture them.
5909:. Vol. 6, no. 7. p. 309. Archived from
5386:
McInerney MJ, Sieber JR, Gunsalus RP (December 2009).
4496:
Liu B, Gibbons T, Ghodsi M, Treangen T, Pop M (2011).
7823:
3405:
Pérez-Cobas AE, Gomez-Valero L, Buchrieser C (2020).
1103:
An emerging approach combines shotgun sequencing and
1011:
Recovery of DNA sequences longer than a few thousand
822:
based methods find less than 1% of the bacterial and
5237:"Compareads: comparing huge metagenomic experiments"
2742:"Exploring prokaryotic diversity in the genomic era"
7754:
7703:
7663:
7551:
7468:
4295:Huson DH, Auch AF, Qi J, Schuster SC (March 2007).
2208:
Metagenomics: Current Innovations and Future Trends
2157:Hugenholtz P, Goebel BM, Pace NR (September 1998).
1953:with primary goals to determine if there is a core
1406:
Genomic Encyclopedia of Bacteria and Archaea (GEBA)
850:. Considerable efforts ensured that these were not
806:(rRNA) sequences which are relatively short, often
6396:Kakirde KS, Parsley LC, Liles MR (November 2010).
3641:. Washington, D.C.: The National Academies Press.
3167:"Unlocking short read sequencing for metagenomics"
1273:with genes that are already publicly available in
941:never before seen. Venter thoroughly explored the
6654:"What's Swimming in the River? Just Look For DNA"
1630:in a saline desert and in Antarctic dry valleys.
921:, leader of the privately funded parallel of the
3630:
3628:
3626:
3624:
3622:
3620:
3618:
3356:Hiraoka S, Yang CC, Iwasaki W (September 2016).
1763:. Microbes also produce a variety of sources of
5962:TerraGenome international sequencing consortium
5186:Fimereli D, Detours V, Konopka T (April 2013).
4434:
4432:
2152:
2150:
2018:sequences with associated clinical phenotypes.
6832:Metagenomics: Theory, Methods and Applications
6781:Metagenomics: Theory, Methods and Applications
6391:
6389:
6387:
6336:"Biotechnological prospects from metagenomics"
6329:
6327:
6308:Metagenomics: Theory, Methods and Applications
6022:Metagenomics: Theory, Methods and Applications
5994:. The National Academies Press. Archived from
5980:
5978:
5286:Kuntal BK, Ghosh TS, Mande SS (October 2013).
5035:"Metagenomic analyses: past and future trends"
3568:
3566:
3011:Thomas T, Gilbert J, Meyer F (February 2012).
1671:understood despite their economic importance.
1111:, and Nanopore MinION, GridION, PromethION by
486:had been missed by cultivation-based methods.
7446:
5388:"Syntrophy in anaerobic global carbon cycles"
5090:Willner D, Thurber RV, Rohwer F (July 2009).
4194:Zhu W, Lomsadze A, Borodovsky M (July 2010).
3941:
3939:
3937:
3935:
3933:
3111:
3109:
2904:
2902:
2900:
768:
440:. The broad field may also be referred to as
346:
8:
7096:Chiu, Charles Y.; Miller, Steven A. (2019).
6445:Parachin NS, Gorwa-Grauslund MF (May 2011).
5028:
5026:
5024:
5022:
5020:
5018:
4745:
4743:
4290:
4288:
4140:
4138:
3948:"A bioinformatician's guide to metagenomics"
2681:
2679:
2090:
2088:
2086:
2084:
2082:
2080:
2078:
1019:was very difficult until recent advances in
1001:Flow diagram of a typical metagenome project
7726:Matrix-assisted laser desorption ionization
3454:
3452:
2450:. Vol. 9. Springer US. pp. 1–55.
1581:of mRNA, for example) in the collection of
7794:
7453:
7439:
7431:
3952:Microbiology and Molecular Biology Reviews
1626:showed the first evidence of existence of
775:
761:
541:
510:The term "metagenomics" was first used by
353:
339:
20:
7386:
7345:
7288:
7278:
7237:
7188:
7131:
7113:
7017:
7007:
6957:
6900:
6747:
6706:
6696:
6629:
6619:
6570:
6521:
6472:
6462:
6421:
6282:
6233:
6223:
6182:
6172:
6123:
6113:
6072:
6062:
5941:
5839:
5786:
5749:
5650:
5601:
5411:
5362:
5352:
5303:
5262:
5252:
5211:
5162:
5152:
5115:
5066:
4998:
4957:
4928:
4918:
4877:
4867:
4826:
4777:
4767:
4723:
4674:
4664:
4623:
4574:
4564:
4523:
4513:
4472:
4369:
4320:
4268:
4219:
4170:
4118:
4069:
4020:
3971:
3913:
3903:
3811:
3762:
3752:
3703:
3598:
3543:
3432:
3422:
3381:
3332:
3283:
3200:
3190:
3141:
3038:
3028:
3017:Microbial Informatics and Experimentation
2987:
2977:
2877:
2812:
2767:
2757:
2659:
2649:
2600:
2507:
2422:
2412:
2363:
2353:
2303:
2262:
2252:
2182:
2130:
2120:
1780:efficient industrial-scale deconstruction
1398:Integrated Microbial Genomes/Metagenomes
1162:
996:
369:In metagenomics, the genetic materials (
7830:
2074:
1023:techniques allowed the construction of
933:, found DNA from nearly 2000 different
626:
578:
549:
436:or clinical samples by a method called
28:
16:Study of genes found in the environment
6853:
6851:
6334:Schloss PD, Handelsman J (June 2003).
6263:Applied Microbiology and Biotechnology
5879:Copeland CS (September–October 2017).
5039:Applied and Environmental Microbiology
4245:"What is microbial community ecology?"
2534:Applied Microbiology and Biotechnology
1856:Two types of analysis are used in the
1679:necessary for plant growth, including
7768:European Molecular Biology Laboratory
7043:"Taking metagenomics under the wings"
3878:Schmieder R, Edwards R (March 2011).
862:. After leaving the Pace laboratory,
7:
7261:Parry R, James ME, Asgari S (2021).
4850:Bazinet AL, Cummings MP (May 2012).
4297:"MEGAN analysis of metagenomic data"
1945:play a key role in preserving human
1735:conversion, as in the conversion of
882:, and colleagues used environmental
7427:to evaluate methods in metagenomics
6806:"How Microbes Defend and Define Us"
6257:Simon C, Daniel R (November 2009).
5147:. 12 Suppl 13 (Supplement 13): S9.
5033:Simon C, Daniel R (February 2011).
3684:Bioinformatics and Biology Insights
1086:Ion Torrent Personal Genome Machine
6045:Bringel F, Couée I (22 May 2015).
2482:, DeLong EF, Pace NR (July 1991).
1903:, and track seasonal populations.
973:, in this case massively parallel
900:University of California, Berkeley
729:Consortium for the Barcode of Life
532:University of California, Berkeley
14:
5888:Healthcare Journal of New Orleans
4044:Zerbino DR, Birney E (May 2008).
3268:"Metagenomics versus Moore's law"
432:material recovered directly from
7845:
7833:
7806:
7805:
7793:
6343:Current Opinion in Biotechnology
5437:Current Opinion in Biotechnology
5392:Current Opinion in Biotechnology
5117:10.1111/j.1462-2920.2009.01901.x
3958:(4): 557–78, Table of Contents.
3084:10.1046/j.1462-2920.2000.00133.x
2500:10.1128/jb.173.14.4371-4378.1991
2175:10.1128/JB.180.18.4765-4774.1998
1127:
1029:bacterial artificial chromosomes
927:Global Ocean Sampling Expedition
906:sequenced DNA extracted from an
742:
741:
557:
320:
319:
206:
205:
36:
7746:Chromosome conformation capture
6402:Soil Biology & Biochemistry
2759:10.1186/gb-2002-3-2-reviews0003
2328:Chen K, Pachter L (July 2005).
2015:Clinical metagenomic sequencing
1706:and the adaptation of enhanced
1585:there have been relatively few
1423:classifications, respectively.
1105:chromosome conformation capture
965:In 2005 Stephan C. Schuster at
943:West Coast of the United States
7388:10.1016/j.jviromet.2017.08.019
6736:Metabarcoding and Metagenomics
1961:tools to support these goals.
1617:for bacteria and archaea, and
1569:) provides information on the
1334:. Another tool, PhymmBL, uses
1031:(BACs), which provided better
833:in the field was conducted by
1:
7774:National Institutes of Health
7280:10.3390/microorganisms9081653
6414:10.1016/j.soilbio.2010.07.021
6355:10.1016/S0958-1669(03)00067-3
3804:10.1093/bioinformatics/btt047
2593:10.1128/jb.178.3.591-599.1996
2448:Advances in Microbial Ecology
2305:10.1016/S1074-5521(98)90108-9
7009:10.1371/journal.pcbi.1002358
6982:Huttenhower, Curtis (2012).
6621:10.1371/journal.pone.0036478
6225:10.1371/journal.pgen.1001129
6174:10.1371/journal.pone.0014519
5449:10.1016/j.copbio.2011.04.018
5404:10.1016/j.copbio.2009.10.001
5254:10.1186/1471-2105-13-S19-S10
3905:10.1371/journal.pone.0017288
3754:10.1371/journal.pone.0031386
3192:10.1371/journal.pone.0011840
2355:10.1371/journal.pcbi.0010024
2254:10.1371/journal.pbio.0050082
2122:10.1371/journal.pcbi.1000667
2005:Infectious disease diagnosis
1938:Gut microbe characterization
1853:is increasingly recognized.
1597:transcriptomics technologies
1550:Transcriptomics technologies
1402:Integrated Microbial Genomes
1113:Oxford Nanopore Technologies
7690:Structure-based drug design
7418:Nature Reviews Microbiology
7047:Nature Reviews Microbiology
6685:Molecular Ecology Resources
5930:Nature Reviews Microbiology
5523:"Uncovering Earth's virome"
5305:10.1016/j.ygeno.2013.08.004
5154:10.1186/1471-2105-12-s13-s9
4769:10.1186/1471-2105-12-S1-S21
4243:Konopka A (November 2009).
2456:10.1007/978-1-4757-0611-6_1
1951:Human Microbiome initiative
1687:, disease suppression, and
1681:fixing atmospheric nitrogen
1386:Argonne National Laboratory
7904:
7883:Environmental microbiology
7338:10.1038/s41598-019-55741-3
7181:10.1038/s41598-018-22945-y
7059:10.1038/s41579-022-00746-5
6988:PLOS Computational Biology
6834:. Caister Academic Press.
6783:. Caister Academic Press.
6451:Biotechnology for Biofuels
6310:. Caister Academic Press.
6102:Biotechnology for Biofuels
6024:. Caister Academic Press.
5096:Environmental Microbiology
4813:(Database issue): D36-42.
4710:(Database issue): D123-9.
4610:(Database issue): D571-9.
4515:10.1186/1471-2164-12-S2-S4
4465:10.1038/s41467-019-08844-4
3325:10.1038/s41467-018-03317-6
3064:Environmental Microbiology
2334:PLOS Computational Biology
2101:PLOS Computational Biology
2097:"A primer on metagenomics"
1910:
1782:of biomass requires novel
1717:
1675:perform a wide variety of
1606:
1553:
1543:
1474:shared by pairs of reads.
1336:interpolated Markov models
1311:
1258:
1203:
1078:high-throughput sequencing
1071:High-throughput sequencing
1004:
987:San Diego State University
971:high-throughput sequencing
699:High throughput sequencing
526:. In 2005, Kevin Chen and
397:) after multiplication by
7789:
7780:Wellcome Sanger Institute
7115:10.1038/s41576-019-0113-7
6804:Zimmer C (13 July 2010).
6551:Molecular Systems Biology
6514:10.1038/s41564-018-0110-1
6275:10.1007/s00253-009-2233-z
6051:Frontiers in Microbiology
5850:10.1007/s00705-017-3286-4
5797:10.1007/s00705-015-2720-8
5742:10.1016/j.tim.2009.11.003
4920:10.1186/s12864-015-1419-2
3849:10.1007/s12038-011-9105-2
3362:Microbes and Environments
3122:Molecular Systems Biology
1907:Environmental remediation
1747:, and other biomass into
1175:metagenome generated 279
937:, including 148 types of
837:and colleagues, who used
7736:Microfluidic-based tools
7581:Human Connectome Project
7513:Human Microbiome Project
6064:10.3389/fmicb.2015.00486
1978:Human Microbiome Project
1435:Comparative metagenomics
1299:. The main advantage of
1217:repetitive DNA sequences
1094:Applied Biosystems SOLiD
1080:used massively parallel
856:non-protein coding genes
636:Environmental DNA (eDNA)
405:) in an approach called
7888:Microbiology techniques
7721:Electrospray ionization
7593:Human Epigenome Project
7102:Nature Reviews Genetics
7098:"Clinical metagenomics"
6698:10.1111/1755-0998.13425
5354:10.1073/pnas.1015676108
4869:10.1186/1471-2105-13-92
4666:10.1186/1471-2105-9-386
3559:(subscription required)
3481:10.1126/science.1200387
2931:10.1126/science.1123360
2893:(subscription required)
2823:10.1126/science.1093857
2729:(subscription required)
2581:Journal of Bacteriology
2488:Journal of Bacteriology
2414:10.1073/pnas.82.20.6955
2292:Chemistry & Biology
2235:Eisen JA (March 2007).
2163:Journal of Bacteriology
2049:Epidemiology and sewage
1991:evidence-based medicine
1863:conserved DNA sequences
1802:microbial systems like
1092:MiSeq or HiSeq and the
7762:DNA Data Bank of Japan
7678:Human proteome project
7481:Computational genomics
6691:(7): 1755–0998.13425.
6115:10.1186/1754-6834-2-10
5958:"TerraGenome Homepage"
5730:Trends in Microbiology
5695:10.1038/nprot.2017.063
5631:Nucleic Acids Research
5582:Nucleic Acids Research
5192:Nucleic Acids Research
4807:Nucleic Acids Research
4704:Nucleic Acids Research
4604:Nucleic Acids Research
4200:Nucleic Acids Research
4001:Nucleic Acids Research
3837:Journal of Biosciences
2979:10.1186/1471-2164-7-57
2651:10.1073/pnas.202488399
2212:Caister Academic Press
2206:Marco, D, ed. (2011).
2022:Arbovirus surveillance
1887:
1188:Sequence pre-filtering
1168:
1138:is missing information
1002:
904:Joint Genome Institute
518:, Michelle R. Rondon,
484:microbial biodiversity
442:environmental genomics
422:
7741:Isotope affinity tags
7695:Expression proteomics
7413:Focus on Metagenomics
6464:10.1186/1754-6834-4-9
5881:"The World Within Us"
4991:10.1093/dnares/dsm018
4445:Nature Communications
4270:10.1038/ismej.2009.88
4163:10.1101/gr.120618.111
4111:10.1534/g3.114.011825
4062:10.1101/gr.074492.107
3964:10.1128/MMBR.00009-08
3424:10.1099/mgen.0.000409
3374:10.1264/jsme2.ME16024
3305:Nature Communications
3285:10.1038/nmeth0909-623
3030:10.1186/2042-5783-2-3
2740:Hugenholtz P (2002).
1995:personalized medicine
1943:Microbial communities
1885:
1846:where the benefit of
1544:Further information:
1404:(IMG) system and the
1390:University of Chicago
1265:Metagenomic analysis
1166:
1000:
967:Penn State University
471:rely upon cultivated
368:
306:Personalized medicine
300:Personalized medicine
163:Quantitative genetics
158:Mendelian inheritance
7501:Human Genome Project
7486:Comparative genomics
7230:10.1128/JCM.01893-20
6749:10.3897/mbmg.6.78756
5828:Archives of Virology
5775:Archives of Virology
5059:10.1128/AEM.02345-10
1796:glycoside hydrolases
1491:Community metabolism
1043:Shotgun metagenomics
1021:molecular biological
985:, and colleagues at
923:Human Genome Project
530:(researchers at the
226:Branches of genetics
7711:2-D electrophoresis
7685:Call-map proteomics
7543:Structural genomics
7530:Population genomics
7491:Functional genomics
7330:2019NatSR...919398B
7212:Thoendel M (2020).
7173:2018NatSR...8.4690Z
7000:2012PLSCB...8E2358A
6950:10.1038/nature08821
6942:2010Natur.464...59.
6885:10.1038/nature08821
6877:2010Natur.464...59.
6612:2012PLoSO...736478L
6502:Nature Microbiology
6165:2011PLoSO...614519J
5943:10.1038/nrmicro2119
5643:10.1093/nar/gky1127
5594:10.1093/nar/gkw1030
5547:10.1038/nature19094
5539:2016Natur.536..425P
5492:10.1038/nature04983
5484:2006Natur.442..806L
5345:2011PNAS..108.4158W
5108:2009EnvMi..11.1752W
5051:2011ApEnM..77.1153S
4819:10.1093/nar/gks1195
4616:10.1093/nar/gkr1100
4457:2019NatCo..10.1014M
4261:2009ISMEJ...3.1223K
3896:2011PLoSO...617288S
3745:2012PLoSO...731386M
3536:10.1038/nature08821
3528:2010Natur.464...59.
3473:2011Sci...331..463H
3317:2018NatCo...9..870S
3183:2010PLoSO...511840R
3134:10.1038/msb.2013.22
3076:2000EnvMi...2..516B
2923:2006Sci...311..392P
2879:10.1038/nature09530
2870:2010Natur.468...60Y
2805:2004Sci...304...66V
2708:10.1038/nature02340
2700:2004Natur.428...37T
2642:2002PNAS...9914250B
2405:1985PNAS...82.6955L
2346:2005PLSCB...1...24C
2113:2010PLSCB...6E0667W
1973:bacterial genomes.
1934:trials to succeed.
1759:of the sugars into
1673:Microbial consortia
1556:Metatranscriptomics
1540:Metatranscriptomics
1513:Syntrophobacterales
1109:Pacific Biosciences
1015:from environmental
917:Beginning in 2003,
829:In the 1980s early
669:Metatranscriptomics
545:Part of a series on
385:) after filtering (
196:Genetic engineering
153:Population genetics
24:Part of a series on
7665:Structural biology
7476:Cognitive genomics
6563:10.1038/msb.2011.6
6001:on 30 October 2012
5901:Jansson J (2011).
5241:BMC Bioinformatics
5204:10.1093/nar/gkt094
5145:BMC Bioinformatics
4856:BMC Bioinformatics
4756:BMC Bioinformatics
4716:10.1093/nar/gkr975
4653:BMC Bioinformatics
4566:10.7717/peerj.3138
4407:10.1038/nmeth.2693
4362:10.1038/nmeth.2066
4313:10.1101/gr.5969107
4212:10.1093/nar/gkq275
4013:10.1093/nar/gks678
3696:10.4137/BBI.S12462
3591:10.1038/nmeth.2658
3411:Microbial Genomics
2752:(2): REVIEWS0003.
2546:10.1007/BF00164771
1901:endangered species
1888:
1867:design PCR primers
1755:, followed by the
1749:cellulosic ethanol
1677:ecosystem services
1624:Giant Virus Finder
1609:Viral metagenomics
1468:similarity measure
1275:sequence databases
1169:
1082:454 pyrosequencing
1065:consensus sequence
1053:shotgun sequencing
1003:
908:acid mine drainage
884:shotgun sequencing
848:Indiana University
694:Shotgun sequencing
611:macroinvertebrates
459:While traditional
450:community genomics
423:
407:shotgun sequencing
168:Molecular genetics
127:History and topics
7821:
7820:
7716:Mass spectrometer
7525:Personal genomics
6841:978-1-904455-54-7
6790:978-1-904455-54-7
6408:(11): 1911–1923.
6317:978-1-904455-54-7
6031:978-1-904455-54-7
5913:on 31 March 2012.
5637:(D1): D678–D686.
5588:(D1): D457–D465.
5247:(Suppl 19): S10.
3656:978-0-309-10676-4
3238:10.1038/nmeth1156
2465:978-1-4757-0611-6
2221:978-1-904455-87-5
2059:Microbial ecology
1986:glycosaminoglycan
1583:environmental RNA
1567:metatranscriptome
1338:to assign reads.
1320:species diversity
1314:Species diversity
1308:Species diversity
1206:Sequence assembly
1161:
1160:
1098:Sanger sequencing
1037:molecular cloning
979:454 Life Sciences
894:, including many
785:
784:
708:Extracellular RNA
642:environmental RNA
516:Robert M. Goodman
492:microbial ecology
465:genome sequencing
419:species diversity
363:
362:
90:Genetic variation
7895:
7850:
7849:
7848:
7838:
7837:
7829:
7809:
7808:
7797:
7796:
7640:Pharmacogenomics
7635:Pharmacogenetics
7455:
7448:
7441:
7432:
7401:
7400:
7390:
7366:
7360:
7359:
7349:
7309:
7303:
7302:
7292:
7282:
7258:
7252:
7251:
7241:
7218:J Clin Microbiol
7209:
7203:
7202:
7192:
7152:
7146:
7145:
7135:
7117:
7093:
7087:
7086:
7038:
7032:
7031:
7021:
7011:
6978:
6972:
6971:
6961:
6921:
6915:
6914:
6904:
6855:
6846:
6845:
6827:
6821:
6820:
6818:
6816:
6801:
6795:
6794:
6776:
6770:
6769:
6751:
6727:
6721:
6720:
6710:
6700:
6676:
6670:
6669:
6667:
6665:
6650:
6644:
6643:
6633:
6623:
6591:
6585:
6584:
6574:
6542:
6536:
6535:
6525:
6493:
6487:
6486:
6476:
6466:
6442:
6436:
6435:
6425:
6393:
6382:
6381:
6379:
6377:
6371:
6365:. Archived from
6340:
6331:
6322:
6321:
6303:
6297:
6296:
6286:
6254:
6248:
6247:
6237:
6227:
6203:
6197:
6196:
6186:
6176:
6144:
6138:
6137:
6127:
6117:
6093:
6087:
6086:
6076:
6066:
6042:
6036:
6035:
6017:
6011:
6010:
6008:
6006:
6000:
5993:
5982:
5973:
5972:
5970:
5968:
5954:
5948:
5947:
5945:
5921:
5915:
5914:
5898:
5892:
5891:
5885:
5876:
5870:
5869:
5843:
5834:(6): 1671–1676.
5823:
5817:
5816:
5790:
5770:
5764:
5763:
5753:
5721:
5715:
5714:
5689:(8): 1673–1682.
5683:Nature Protocols
5680:
5671:
5665:
5664:
5654:
5622:
5616:
5615:
5605:
5573:
5567:
5566:
5533:(7617): 425–30.
5518:
5512:
5511:
5467:
5461:
5460:
5432:
5426:
5425:
5415:
5383:
5377:
5376:
5366:
5356:
5324:
5318:
5317:
5307:
5283:
5277:
5276:
5266:
5256:
5232:
5226:
5225:
5215:
5183:
5177:
5176:
5166:
5156:
5136:
5130:
5129:
5119:
5087:
5081:
5080:
5070:
5030:
5013:
5012:
5002:
4970:
4964:
4963:
4961:
4949:
4943:
4942:
4932:
4922:
4898:
4892:
4891:
4881:
4871:
4847:
4841:
4840:
4830:
4798:
4792:
4791:
4781:
4771:
4762:(Suppl 1): S21.
4747:
4738:
4737:
4727:
4695:
4689:
4688:
4678:
4668:
4644:
4638:
4637:
4627:
4595:
4589:
4588:
4578:
4568:
4544:
4538:
4537:
4527:
4517:
4493:
4487:
4486:
4476:
4436:
4427:
4426:
4390:
4384:
4383:
4373:
4341:
4335:
4334:
4324:
4292:
4283:
4282:
4272:
4249:The ISME Journal
4240:
4234:
4233:
4223:
4191:
4185:
4184:
4174:
4142:
4133:
4132:
4122:
4090:
4084:
4083:
4073:
4041:
4035:
4034:
4024:
3992:
3986:
3985:
3975:
3943:
3928:
3927:
3917:
3907:
3875:
3869:
3868:
3832:
3826:
3825:
3815:
3783:
3777:
3776:
3766:
3756:
3724:
3718:
3717:
3707:
3675:
3669:
3668:
3632:
3613:
3612:
3602:
3570:
3561:
3560:
3557:
3547:
3507:
3501:
3500:
3456:
3447:
3446:
3436:
3426:
3402:
3396:
3395:
3385:
3353:
3347:
3346:
3336:
3296:
3290:
3289:
3287:
3278:(9): 623. 2009.
3264:
3258:
3257:
3221:
3215:
3214:
3204:
3194:
3162:
3156:
3155:
3145:
3113:
3104:
3103:
3059:
3053:
3052:
3042:
3032:
3008:
3002:
3001:
2991:
2981:
2957:
2951:
2950:
2906:
2895:
2894:
2891:
2881:
2849:
2843:
2842:
2816:
2788:
2782:
2781:
2771:
2761:
2737:
2731:
2730:
2727:
2683:
2674:
2673:
2663:
2653:
2621:
2615:
2614:
2604:
2572:
2566:
2565:
2528:
2522:
2521:
2511:
2476:
2470:
2469:
2443:
2437:
2436:
2426:
2416:
2384:
2378:
2377:
2367:
2357:
2325:
2319:
2317:
2307:
2283:
2277:
2276:
2266:
2256:
2232:
2226:
2225:
2203:
2197:
2196:
2186:
2154:
2145:
2144:
2134:
2124:
2092:
1982:human microbiome
1955:human microbiome
1897:invasive species
1851:chiral synthesis
1848:enzyme-catalyzed
1685:nutrient cycling
1366:Data integration
1360:codon usage bias
1249:de Bruijn graphs
1245:Velvet assembler
1156:
1153:
1147:
1131:
1123:
777:
770:
763:
750:
745:
744:
561:
542:
428:is the study of
411:assembly methods
355:
348:
341:
328:
323:
322:
218:Medical genetics
214:
209:
208:
40:
21:
7903:
7902:
7898:
7897:
7896:
7894:
7893:
7892:
7858:
7857:
7856:
7846:
7844:
7832:
7824:
7822:
7817:
7785:
7750:
7699:
7659:
7655:Transcriptomics
7645:Systems biology
7630:Paleopolyploidy
7566:Cheminformatics
7547:
7464:
7459:
7421:journal website
7409:
7404:
7375:J Virol Methods
7368:
7367:
7363:
7311:
7310:
7306:
7260:
7259:
7255:
7211:
7210:
7206:
7154:
7153:
7149:
7095:
7094:
7090:
7040:
7039:
7035:
6994:(6): e1002358.
6980:
6979:
6975:
6936:(7285): 59–65.
6923:
6922:
6918:
6871:(7285): 59–65.
6857:
6856:
6849:
6842:
6829:
6828:
6824:
6814:
6812:
6803:
6802:
6798:
6791:
6778:
6777:
6773:
6729:
6728:
6724:
6678:
6677:
6673:
6663:
6661:
6652:
6651:
6647:
6593:
6592:
6588:
6544:
6543:
6539:
6495:
6494:
6490:
6444:
6443:
6439:
6395:
6394:
6385:
6375:
6373:
6372:on 4 March 2016
6369:
6338:
6333:
6332:
6325:
6318:
6305:
6304:
6300:
6256:
6255:
6251:
6218:(9): e1001129.
6205:
6204:
6200:
6146:
6145:
6141:
6095:
6094:
6090:
6044:
6043:
6039:
6032:
6019:
6018:
6014:
6004:
6002:
5998:
5991:
5984:
5983:
5976:
5966:
5964:
5956:
5955:
5951:
5923:
5922:
5918:
5900:
5899:
5895:
5883:
5878:
5877:
5873:
5825:
5824:
5820:
5772:
5771:
5767:
5723:
5722:
5718:
5678:
5673:
5672:
5668:
5624:
5623:
5619:
5575:
5574:
5570:
5520:
5519:
5515:
5478:(7104): 806–9.
5469:
5468:
5464:
5434:
5433:
5429:
5385:
5384:
5380:
5339:(10): 4158–63.
5326:
5325:
5321:
5285:
5284:
5280:
5234:
5233:
5229:
5185:
5184:
5180:
5138:
5137:
5133:
5089:
5088:
5084:
5032:
5031:
5016:
4972:
4971:
4967:
4951:
4950:
4946:
4900:
4899:
4895:
4849:
4848:
4844:
4800:
4799:
4795:
4749:
4748:
4741:
4697:
4696:
4692:
4646:
4645:
4641:
4597:
4596:
4592:
4546:
4545:
4541:
4508:(Suppl 2): S4.
4495:
4494:
4490:
4438:
4437:
4430:
4392:
4391:
4387:
4343:
4342:
4338:
4301:Genome Research
4294:
4293:
4286:
4255:(11): 1223–30.
4242:
4241:
4237:
4193:
4192:
4188:
4151:Genome Research
4144:
4143:
4136:
4092:
4091:
4087:
4050:Genome Research
4043:
4042:
4038:
3994:
3993:
3989:
3945:
3944:
3931:
3877:
3876:
3872:
3834:
3833:
3829:
3785:
3784:
3780:
3726:
3725:
3721:
3677:
3676:
3672:
3657:
3634:
3633:
3616:
3572:
3571:
3564:
3558:
3522:(7285): 59–65.
3509:
3508:
3504:
3467:(6016): 463–7.
3458:
3457:
3450:
3404:
3403:
3399:
3355:
3354:
3350:
3298:
3297:
3293:
3266:
3265:
3261:
3223:
3222:
3218:
3164:
3163:
3159:
3115:
3114:
3107:
3061:
3060:
3056:
3010:
3009:
3005:
2959:
2958:
2954:
2917:(5759): 392–4.
2908:
2907:
2898:
2892:
2851:
2850:
2846:
2814:10.1.1.124.1840
2799:(5667): 66–74.
2790:
2789:
2785:
2739:
2738:
2734:
2728:
2694:(6978): 37–43.
2685:
2684:
2677:
2636:(22): 14250–5.
2623:
2622:
2618:
2574:
2573:
2569:
2530:
2529:
2525:
2478:
2477:
2473:
2466:
2445:
2444:
2440:
2386:
2385:
2381:
2327:
2326:
2322:
2285:
2284:
2280:
2234:
2233:
2229:
2222:
2205:
2204:
2200:
2169:(18): 4765–74.
2156:
2155:
2148:
2107:(2): e1000667.
2094:
2093:
2076:
2072:
2040:
2024:
2007:
1940:
1928:bioaugmentation
1915:
1909:
1880:
1844:pharmaceuticals
1827:
1819:leafcutter ants
1722:
1716:
1664:
1636:
1611:
1605:
1579:short half-life
1558:
1552:
1542:
1493:
1488:
1437:
1368:
1316:
1310:
1285:4. The second,
1263:
1261:Gene prediction
1257:
1255:Gene prediction
1229:paired-end tags
1208:
1202:
1190:
1157:
1151:
1148:
1141:
1132:
1121:
1073:
1045:
1009:
995:
892:marine sediment
781:
740:
733:
724:Diet assessment
715:
703:
689:
673:
664:
648:
638:
622:
574:
572:
564:
540:
508:
359:
318:
311:
310:
301:
293:
292:
291:
290:
239:
231:
230:
222:
200:
181:
173:
172:
128:
120:
119:
106:
105:
104:
48:
17:
12:
11:
5:
7901:
7899:
7891:
7890:
7885:
7880:
7875:
7873:Bioinformatics
7870:
7860:
7859:
7855:
7854:
7842:
7819:
7818:
7816:
7815:
7803:
7790:
7787:
7786:
7784:
7783:
7777:
7771:
7765:
7758:
7756:
7752:
7751:
7749:
7748:
7743:
7738:
7733:
7728:
7723:
7718:
7713:
7707:
7705:
7704:Research tools
7701:
7700:
7698:
7697:
7692:
7687:
7682:
7681:
7680:
7669:
7667:
7661:
7660:
7658:
7657:
7652:
7650:Toxicogenomics
7647:
7642:
7637:
7632:
7627:
7622:
7617:
7612:
7607:
7602:
7597:
7596:
7595:
7585:
7584:
7583:
7573:
7568:
7563:
7557:
7555:
7553:Bioinformatics
7549:
7548:
7546:
7545:
7540:
7532:
7527:
7522:
7517:
7516:
7515:
7505:
7504:
7503:
7496:Genome project
7493:
7488:
7483:
7478:
7472:
7470:
7466:
7465:
7460:
7458:
7457:
7450:
7443:
7435:
7429:
7428:
7422:
7408:
7407:External links
7405:
7403:
7402:
7361:
7304:
7267:Microorganisms
7253:
7204:
7147:
7108:(6): 341–355.
7088:
7033:
6973:
6916:
6847:
6840:
6822:
6810:New York Times
6796:
6789:
6771:
6722:
6671:
6660:. 24 July 2013
6645:
6586:
6537:
6508:(4): 415–422.
6488:
6437:
6383:
6323:
6316:
6298:
6249:
6198:
6139:
6088:
6037:
6030:
6012:
5974:
5949:
5916:
5893:
5871:
5818:
5765:
5716:
5666:
5617:
5568:
5513:
5462:
5427:
5378:
5319:
5278:
5227:
5178:
5131:
5102:(7): 1752–66.
5082:
5045:(4): 1153–61.
5014:
4965:
4959:10.1101/267179
4944:
4893:
4842:
4793:
4739:
4690:
4639:
4590:
4539:
4488:
4428:
4401:(12): 1196–9.
4395:Nature Methods
4385:
4350:Nature Methods
4336:
4284:
4235:
4186:
4157:(9): 1552–60.
4134:
4105:(7): 1339–46.
4085:
4036:
3987:
3929:
3870:
3827:
3792:Bioinformatics
3778:
3719:
3670:
3655:
3647:10.17226/11902
3614:
3585:(12): 1200–2.
3579:Nature Methods
3562:
3502:
3448:
3397:
3348:
3291:
3272:Nature Methods
3259:
3226:Nature Methods
3216:
3157:
3105:
3054:
3003:
2952:
2896:
2864:(7320): 60–6.
2844:
2783:
2746:Genome Biology
2732:
2675:
2616:
2567:
2523:
2494:(14): 4371–8.
2471:
2464:
2438:
2399:(20): 6955–9.
2379:
2320:
2298:(10): R245-9.
2278:
2227:
2220:
2198:
2146:
2073:
2071:
2068:
2067:
2066:
2061:
2056:
2054:Metaproteomics
2051:
2046:
2039:
2036:
2023:
2020:
2006:
2003:
1959:bioinformatics
1939:
1936:
1932:biostimulation
1913:Bioremediation
1911:Main article:
1908:
1905:
1879:
1876:
1858:bioprospecting
1836:fine chemicals
1826:
1823:
1806:fermenters or
1718:Main article:
1715:
1712:
1663:
1660:
1652:sustainability
1635:
1632:
1607:Main article:
1604:
1601:
1554:Main article:
1541:
1538:
1492:
1489:
1487:
1484:
1436:
1433:
1367:
1364:
1352:mOTUs profiler
1312:Main article:
1309:
1306:
1259:Main article:
1256:
1253:
1204:Main article:
1201:
1198:
1189:
1186:
1159:
1158:
1135:
1133:
1126:
1120:
1119:Bioinformatics
1117:
1072:
1069:
1049:bioinformatics
1044:
1041:
1007:DNA sequencing
1005:Main article:
994:
991:
975:pyrosequencing
925:, has led the
896:bacteriophages
835:Norman R. Pace
831:molecular work
783:
782:
780:
779:
772:
765:
757:
754:
753:
752:
751:
735:
734:
732:
731:
726:
721:
716:
710:
704:
702:
701:
696:
690:
688:
687:
686:
685:
674:
672:
671:
665:
663:
662:
661:
660:
649:
647:
646:
645:
644:
632:
629:
628:
624:
623:
621:
620:
619:
618:
613:
605:
600:
595:
590:
584:
581:
580:
576:
575:
562:
554:
553:
547:
546:
539:
536:
507:
504:
463:and microbial
361:
360:
358:
357:
350:
343:
335:
332:
331:
330:
329:
313:
312:
309:
308:
302:
299:
298:
295:
294:
289:
288:
283:
278:
273:
268:
266:Immunogenetics
263:
258:
253:
248:
242:
241:
240:
237:
236:
233:
232:
229:
228:
221:
220:
215:
198:
193:
191:DNA sequencing
188:
182:
179:
178:
175:
174:
171:
170:
165:
160:
155:
150:
140:
135:
129:
126:
125:
122:
121:
118:
117:
112:
103:
102:
97:
92:
87:
82:
77:
72:
67:
62:
57:
51:
50:
49:
47:Key components
46:
45:
42:
41:
33:
32:
26:
25:
15:
13:
10:
9:
6:
4:
3:
2:
7900:
7889:
7886:
7884:
7881:
7879:
7876:
7874:
7871:
7869:
7866:
7865:
7863:
7853:
7843:
7841:
7836:
7831:
7827:
7814:
7813:
7804:
7802:
7801:
7792:
7791:
7788:
7781:
7778:
7775:
7772:
7769:
7766:
7763:
7760:
7759:
7757:
7755:Organizations
7753:
7747:
7744:
7742:
7739:
7737:
7734:
7732:
7729:
7727:
7724:
7722:
7719:
7717:
7714:
7712:
7709:
7708:
7706:
7702:
7696:
7693:
7691:
7688:
7686:
7683:
7679:
7676:
7675:
7674:
7671:
7670:
7668:
7666:
7662:
7656:
7653:
7651:
7648:
7646:
7643:
7641:
7638:
7636:
7633:
7631:
7628:
7626:
7625:Nutrigenomics
7623:
7621:
7618:
7616:
7613:
7611:
7608:
7606:
7603:
7601:
7598:
7594:
7591:
7590:
7589:
7586:
7582:
7579:
7578:
7577:
7574:
7572:
7571:Chemogenomics
7569:
7567:
7564:
7562:
7559:
7558:
7556:
7554:
7550:
7544:
7541:
7539:
7537:
7533:
7531:
7528:
7526:
7523:
7521:
7518:
7514:
7511:
7510:
7509:
7506:
7502:
7499:
7498:
7497:
7494:
7492:
7489:
7487:
7484:
7482:
7479:
7477:
7474:
7473:
7471:
7467:
7463:
7456:
7451:
7449:
7444:
7442:
7437:
7436:
7433:
7426:
7423:
7420:
7419:
7414:
7411:
7410:
7406:
7398:
7394:
7389:
7384:
7380:
7376:
7372:
7365:
7362:
7357:
7353:
7348:
7343:
7339:
7335:
7331:
7327:
7323:
7319:
7315:
7308:
7305:
7300:
7296:
7291:
7286:
7281:
7276:
7272:
7268:
7264:
7257:
7254:
7249:
7245:
7240:
7235:
7231:
7227:
7223:
7219:
7215:
7208:
7205:
7200:
7196:
7191:
7186:
7182:
7178:
7174:
7170:
7166:
7162:
7158:
7151:
7148:
7143:
7139:
7134:
7129:
7125:
7121:
7116:
7111:
7107:
7103:
7099:
7092:
7089:
7084:
7080:
7076:
7072:
7068:
7064:
7060:
7056:
7052:
7048:
7044:
7037:
7034:
7029:
7025:
7020:
7015:
7010:
7005:
7001:
6997:
6993:
6989:
6985:
6977:
6974:
6969:
6965:
6960:
6955:
6951:
6947:
6943:
6939:
6935:
6931:
6927:
6920:
6917:
6912:
6908:
6903:
6898:
6894:
6890:
6886:
6882:
6878:
6874:
6870:
6866:
6862:
6854:
6852:
6848:
6843:
6837:
6833:
6826:
6823:
6811:
6807:
6800:
6797:
6792:
6786:
6782:
6775:
6772:
6767:
6763:
6759:
6755:
6750:
6745:
6741:
6737:
6733:
6726:
6723:
6718:
6714:
6709:
6704:
6699:
6694:
6690:
6686:
6682:
6675:
6672:
6659:
6655:
6649:
6646:
6641:
6637:
6632:
6627:
6622:
6617:
6613:
6609:
6606:(5): e36478.
6605:
6601:
6597:
6590:
6587:
6582:
6578:
6573:
6568:
6564:
6560:
6556:
6552:
6548:
6541:
6538:
6533:
6529:
6524:
6519:
6515:
6511:
6507:
6503:
6499:
6492:
6489:
6484:
6480:
6475:
6470:
6465:
6460:
6456:
6452:
6448:
6441:
6438:
6433:
6429:
6424:
6419:
6415:
6411:
6407:
6403:
6399:
6392:
6390:
6388:
6384:
6368:
6364:
6360:
6356:
6352:
6349:(3): 303–10.
6348:
6344:
6337:
6330:
6328:
6324:
6319:
6313:
6309:
6302:
6299:
6294:
6290:
6285:
6280:
6276:
6272:
6269:(2): 265–76.
6268:
6264:
6260:
6253:
6250:
6245:
6241:
6236:
6231:
6226:
6221:
6217:
6213:
6212:PLOS Genetics
6209:
6202:
6199:
6194:
6190:
6185:
6180:
6175:
6170:
6166:
6162:
6159:(1): e14519.
6158:
6154:
6150:
6143:
6140:
6135:
6131:
6126:
6121:
6116:
6111:
6107:
6103:
6099:
6092:
6089:
6084:
6080:
6075:
6070:
6065:
6060:
6056:
6052:
6048:
6041:
6038:
6033:
6027:
6023:
6016:
6013:
5997:
5990:
5989:
5981:
5979:
5975:
5963:
5959:
5953:
5950:
5944:
5939:
5935:
5931:
5927:
5920:
5917:
5912:
5908:
5904:
5897:
5894:
5889:
5882:
5875:
5872:
5867:
5863:
5859:
5855:
5851:
5847:
5842:
5837:
5833:
5829:
5822:
5819:
5814:
5810:
5806:
5802:
5798:
5794:
5789:
5784:
5780:
5776:
5769:
5766:
5761:
5757:
5752:
5747:
5743:
5739:
5735:
5731:
5727:
5720:
5717:
5712:
5708:
5704:
5700:
5696:
5692:
5688:
5684:
5677:
5670:
5667:
5662:
5658:
5653:
5648:
5644:
5640:
5636:
5632:
5628:
5621:
5618:
5613:
5609:
5604:
5599:
5595:
5591:
5587:
5583:
5579:
5572:
5569:
5564:
5560:
5556:
5552:
5548:
5544:
5540:
5536:
5532:
5528:
5524:
5517:
5514:
5509:
5505:
5501:
5497:
5493:
5489:
5485:
5481:
5477:
5473:
5466:
5463:
5458:
5454:
5450:
5446:
5442:
5438:
5431:
5428:
5423:
5419:
5414:
5409:
5405:
5401:
5398:(6): 623–32.
5397:
5393:
5389:
5382:
5379:
5374:
5370:
5365:
5360:
5355:
5350:
5346:
5342:
5338:
5334:
5330:
5323:
5320:
5315:
5311:
5306:
5301:
5298:(4): 409–18.
5297:
5293:
5289:
5282:
5279:
5274:
5270:
5265:
5260:
5255:
5250:
5246:
5242:
5238:
5231:
5228:
5223:
5219:
5214:
5209:
5205:
5201:
5197:
5193:
5189:
5182:
5179:
5174:
5170:
5165:
5160:
5155:
5150:
5146:
5142:
5135:
5132:
5127:
5123:
5118:
5113:
5109:
5105:
5101:
5097:
5093:
5086:
5083:
5078:
5074:
5069:
5064:
5060:
5056:
5052:
5048:
5044:
5040:
5036:
5029:
5027:
5025:
5023:
5021:
5019:
5015:
5010:
5006:
5001:
4996:
4992:
4988:
4985:(4): 169–81.
4984:
4980:
4976:
4969:
4966:
4960:
4955:
4948:
4945:
4940:
4936:
4931:
4926:
4921:
4916:
4912:
4908:
4904:
4897:
4894:
4889:
4885:
4880:
4875:
4870:
4865:
4861:
4857:
4853:
4846:
4843:
4838:
4834:
4829:
4824:
4820:
4816:
4812:
4808:
4804:
4797:
4794:
4789:
4785:
4780:
4775:
4770:
4765:
4761:
4757:
4753:
4746:
4744:
4740:
4735:
4731:
4726:
4721:
4717:
4713:
4709:
4705:
4701:
4694:
4691:
4686:
4682:
4677:
4672:
4667:
4662:
4658:
4654:
4650:
4643:
4640:
4635:
4631:
4626:
4621:
4617:
4613:
4609:
4605:
4601:
4594:
4591:
4586:
4582:
4577:
4572:
4567:
4562:
4558:
4554:
4550:
4543:
4540:
4535:
4531:
4526:
4521:
4516:
4511:
4507:
4503:
4499:
4492:
4489:
4484:
4480:
4475:
4470:
4466:
4462:
4458:
4454:
4450:
4446:
4442:
4435:
4433:
4429:
4424:
4420:
4416:
4412:
4408:
4404:
4400:
4396:
4389:
4386:
4381:
4377:
4372:
4367:
4363:
4359:
4355:
4351:
4347:
4340:
4337:
4332:
4328:
4323:
4318:
4314:
4310:
4307:(3): 377–86.
4306:
4302:
4298:
4291:
4289:
4285:
4280:
4276:
4271:
4266:
4262:
4258:
4254:
4250:
4246:
4239:
4236:
4231:
4227:
4222:
4217:
4213:
4209:
4205:
4201:
4197:
4190:
4187:
4182:
4178:
4173:
4168:
4164:
4160:
4156:
4152:
4148:
4141:
4139:
4135:
4130:
4126:
4121:
4116:
4112:
4108:
4104:
4100:
4096:
4089:
4086:
4081:
4077:
4072:
4067:
4063:
4059:
4055:
4051:
4047:
4040:
4037:
4032:
4028:
4023:
4018:
4014:
4010:
4006:
4002:
3998:
3991:
3988:
3983:
3979:
3974:
3969:
3965:
3961:
3957:
3953:
3949:
3942:
3940:
3938:
3936:
3934:
3930:
3925:
3921:
3916:
3911:
3906:
3901:
3897:
3893:
3890:(3): e17288.
3889:
3885:
3881:
3874:
3871:
3866:
3862:
3858:
3854:
3850:
3846:
3843:(4): 709–17.
3842:
3838:
3831:
3828:
3823:
3819:
3814:
3809:
3805:
3801:
3797:
3793:
3789:
3782:
3779:
3774:
3770:
3765:
3760:
3755:
3750:
3746:
3742:
3739:(2): e31386.
3738:
3734:
3730:
3723:
3720:
3715:
3711:
3706:
3701:
3697:
3693:
3689:
3685:
3681:
3674:
3671:
3666:
3662:
3658:
3652:
3648:
3644:
3640:
3639:
3631:
3629:
3627:
3625:
3623:
3621:
3619:
3615:
3610:
3606:
3601:
3596:
3592:
3588:
3584:
3580:
3576:
3569:
3567:
3563:
3555:
3551:
3546:
3541:
3537:
3533:
3529:
3525:
3521:
3517:
3513:
3506:
3503:
3498:
3494:
3490:
3486:
3482:
3478:
3474:
3470:
3466:
3462:
3455:
3453:
3449:
3444:
3440:
3435:
3430:
3425:
3420:
3416:
3412:
3408:
3401:
3398:
3393:
3389:
3384:
3379:
3375:
3371:
3368:(3): 204–12.
3367:
3363:
3359:
3352:
3349:
3344:
3340:
3335:
3330:
3326:
3322:
3318:
3314:
3310:
3306:
3302:
3295:
3292:
3286:
3281:
3277:
3273:
3269:
3263:
3260:
3255:
3251:
3247:
3243:
3239:
3235:
3231:
3227:
3220:
3217:
3212:
3208:
3203:
3198:
3193:
3188:
3184:
3180:
3177:(7): e11840.
3176:
3172:
3168:
3161:
3158:
3153:
3149:
3144:
3139:
3135:
3131:
3127:
3123:
3119:
3112:
3110:
3106:
3101:
3097:
3093:
3089:
3085:
3081:
3077:
3073:
3070:(5): 516–29.
3069:
3065:
3058:
3055:
3050:
3046:
3041:
3036:
3031:
3026:
3022:
3018:
3014:
3007:
3004:
2999:
2995:
2990:
2985:
2980:
2975:
2971:
2967:
2963:
2956:
2953:
2948:
2944:
2940:
2936:
2932:
2928:
2924:
2920:
2916:
2912:
2905:
2903:
2901:
2897:
2889:
2885:
2880:
2875:
2871:
2867:
2863:
2859:
2855:
2848:
2845:
2840:
2836:
2832:
2828:
2824:
2820:
2815:
2810:
2806:
2802:
2798:
2794:
2787:
2784:
2779:
2775:
2770:
2765:
2760:
2755:
2751:
2747:
2743:
2736:
2733:
2725:
2721:
2717:
2713:
2709:
2705:
2701:
2697:
2693:
2689:
2682:
2680:
2676:
2671:
2667:
2662:
2657:
2652:
2647:
2643:
2639:
2635:
2631:
2627:
2620:
2617:
2612:
2608:
2603:
2598:
2594:
2590:
2586:
2582:
2578:
2571:
2568:
2563:
2559:
2555:
2551:
2547:
2543:
2540:(4): 667–74.
2539:
2535:
2527:
2524:
2519:
2515:
2510:
2505:
2501:
2497:
2493:
2489:
2485:
2481:
2475:
2472:
2467:
2461:
2457:
2453:
2449:
2442:
2439:
2434:
2430:
2425:
2420:
2415:
2410:
2406:
2402:
2398:
2394:
2390:
2383:
2380:
2375:
2371:
2366:
2361:
2356:
2351:
2347:
2343:
2340:(2): 106–12.
2339:
2335:
2331:
2324:
2321:
2315:
2311:
2306:
2301:
2297:
2293:
2289:
2282:
2279:
2274:
2270:
2265:
2260:
2255:
2250:
2246:
2242:
2238:
2231:
2228:
2223:
2217:
2213:
2209:
2202:
2199:
2194:
2190:
2185:
2180:
2176:
2172:
2168:
2164:
2160:
2153:
2151:
2147:
2142:
2138:
2133:
2128:
2123:
2118:
2114:
2110:
2106:
2102:
2098:
2091:
2089:
2087:
2085:
2083:
2081:
2079:
2075:
2069:
2065:
2064:Pathogenomics
2062:
2060:
2057:
2055:
2052:
2050:
2047:
2045:
2042:
2041:
2037:
2035:
2033:
2029:
2028:hematophagous
2021:
2019:
2016:
2012:
2004:
2002:
1998:
1996:
1992:
1987:
1983:
1979:
1974:
1970:
1966:
1962:
1960:
1956:
1952:
1948:
1944:
1937:
1935:
1933:
1929:
1924:
1920:
1914:
1906:
1904:
1902:
1898:
1892:
1884:
1877:
1875:
1874:antibiotics.
1873:
1868:
1864:
1859:
1854:
1852:
1849:
1845:
1841:
1840:agrochemicals
1837:
1833:
1825:Biotechnology
1824:
1822:
1820:
1816:
1815:fungus garden
1812:
1809:
1805:
1801:
1797:
1793:
1789:
1785:
1781:
1776:
1774:
1770:
1766:
1762:
1758:
1754:
1750:
1746:
1742:
1739:contained in
1738:
1734:
1731:derived from
1730:
1726:
1721:
1713:
1711:
1709:
1705:
1701:
1697:
1693:
1690:
1686:
1682:
1678:
1674:
1669:
1661:
1659:
1657:
1653:
1649:
1645:
1641:
1633:
1631:
1629:
1628:giant viruses
1625:
1620:
1616:
1610:
1602:
1600:
1598:
1594:
1590:
1589:
1584:
1580:
1576:
1572:
1568:
1564:
1557:
1551:
1547:
1546:Transcriptome
1539:
1537:
1535:
1530:
1526:
1522:
1518:
1514:
1510:
1506:
1502:
1498:
1490:
1486:Data analysis
1485:
1483:
1481:
1475:
1473:
1469:
1463:
1460:
1456:
1452:
1447:
1443:
1434:
1432:
1428:
1424:
1422:
1418:
1414:
1409:
1407:
1403:
1399:
1395:
1391:
1387:
1381:
1378:
1377:replicability
1373:
1365:
1363:
1361:
1357:
1353:
1349:
1345:
1341:
1337:
1333:
1329:
1325:
1321:
1315:
1307:
1305:
1302:
1298:
1294:
1290:
1289:
1284:
1280:
1277:, usually by
1276:
1272:
1268:
1262:
1254:
1252:
1250:
1246:
1242:
1238:
1234:
1230:
1225:
1223:
1218:
1213:
1207:
1199:
1197:
1195:
1187:
1185:
1182:
1178:
1174:
1165:
1155:
1152:February 2022
1145:
1139:
1136:This section
1134:
1130:
1125:
1124:
1118:
1116:
1114:
1110:
1106:
1101:
1099:
1095:
1091:
1087:
1083:
1079:
1070:
1068:
1066:
1062:
1058:
1054:
1050:
1042:
1040:
1038:
1034:
1030:
1026:
1022:
1018:
1014:
1008:
999:
992:
990:
988:
984:
983:Forest Rohwer
980:
977:developed by
976:
972:
968:
963:
961:
956:
952:
951:Mediterranean
948:
944:
940:
936:
932:
928:
924:
920:
915:
913:
909:
905:
901:
897:
893:
889:
888:viral species
885:
881:
880:Forest Rohwer
877:
876:Mya Breitbart
872:
870:
865:
864:Edward DeLong
861:
857:
853:
849:
845:
840:
836:
832:
827:
825:
821:
817:
813:
809:
805:
802:
798:
794:
790:
787:Conventional
778:
773:
771:
766:
764:
759:
758:
756:
755:
749:
739:
738:
737:
736:
730:
727:
725:
722:
720:
717:
714:
711:
709:
706:
705:
700:
697:
695:
692:
691:
684:
681:
680:
679:
678:Amplification
676:
675:
670:
667:
666:
659:
656:
655:
654:
651:
650:
643:
640:
639:
637:
634:
633:
631:
630:
625:
617:
614:
612:
609:
608:
606:
604:
601:
599:
596:
594:
591:
589:
586:
585:
583:
582:
577:
571:
570:Metabarcoding
567:
566:DNA barcoding
560:
556:
555:
552:
551:DNA barcoding
548:
544:
543:
537:
535:
533:
529:
525:
521:
517:
513:
512:Jo Handelsman
505:
503:
501:
497:
493:
487:
485:
481:
477:
474:
470:
466:
462:
457:
455:
451:
447:
443:
439:
435:
434:environmental
431:
427:
420:
416:
412:
408:
404:
400:
396:
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1061:reconstructs
1057:human genome
1047:Advances in
1046:
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931:Sargasso Sea
919:Craig Venter
916:
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828:
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653:Metagenomics
652:
528:Lior Pachter
509:
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461:microbiology
458:
454:microbiomics
453:
449:
445:
441:
426:Metagenomics
425:
424:
414:
402:
394:
386:
382:
374:
286:Quantitative
256:Cytogenetics
251:Conservation
133:Introduction
18:
7588:Epigenomics
7520:Pangenomics
7273:(8): 1653.
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6815:29 December
6005:30 December
5967:30 December
5736:(1): 11–9.
4451:(1): 1014.
3232:(1): 16–8.
2032:arboviruses
1745:switchgrass
1662:Agriculture
1648:agriculture
1644:engineering
1532:tool (with
1525:microarrays
1517:Synergistia
1497:bioreactors
820:cultivation
446:ecogenomics
389:), and are
7862:Categories
7673:Proteomics
7610:Lipidomics
7605:Immunomics
7053:(8): 447.
6742:: e78756.
6664:10 October
6376:20 January
5936:(4): 252.
5841:1503.05575
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2480:Schmidt TM
2247:(3): e82.
2070:References
1923:ecosystems
1919:pollutants
1811:herbivores
1800:convergent
1767:including
1694:and other
1593:microarray
1575:expression
1571:regulation
1529:proteomics
1509:syntrophic
1442:GC-content
1194:eukaryotic
1181:microbiome
1013:base pairs
993:Sequencing
789:sequencing
719:Healthcare
520:Jon Clardy
438:sequencing
281:Population
261:Ecological
186:Geneticist
100:Amino acid
80:Nucleotide
55:Chromosome
7600:Glycomics
7381:: 79–84.
7124:1471-0064
7083:248739527
7067:1740-1534
6893:1476-4687
6766:248041252
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4803:"GenBank"
4559:: e3138.
3690:: 75–88.
2809:CiteSeerX
1872:malacidin
1832:commodity
1788:screening
1765:bioenergy
1737:cellulose
1704:livestock
1689:sequester
1511:species (
1501:syntrophy
1459:community
1408:project.
1340:MetaPhlAn
1301:ab initio
1288:ab initio
1267:pipelines
1177:gigabases
1144:talk page
1025:libraries
874:In 2002,
871:samples.
808:conserved
801:ribosomal
588:Microbial
506:Etymology
391:sequenced
379:extracted
276:Molecular
271:Microbial
246:Classical
147:molecular
143:Evolution
7878:Genomics
7852:Medicine
7812:Category
7538:genomics
7462:Genomics
7397:28855093
7356:31852942
7299:34442732
7248:32878948
7199:29549363
7142:30918369
7075:35546350
7028:22719234
6968:20203603
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6600:PLOS ONE
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5292:Genomics
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2374:16110337
2273:17355177
2141:20195499
2038:See also
1773:hydrogen
1743:stalks,
1725:Biofuels
1640:medicine
1446:16S rRNA
1388:and the
1372:metadata
1293:GeneMark
1271:homology
1212:coverage
1200:Assembly
1090:Illumina
960:plankton
939:bacteria
902:and the
824:archaeal
797:cultured
748:Category
607:Aquatic
480:16S rRNA
476:cultures
469:genomics
326:Category
211:template
202:Genomics
180:Research
85:Mutation
75:Heredity
30:Genetics
7840:Biology
7826:Portals
7561:Biochip
7347:6920425
7326:Bibcode
7318:Sci Rep
7290:8398489
7239:7587107
7190:5856816
7169:Bibcode
7161:Sci Rep
7133:6858796
7019:3374609
6996:Bibcode
6959:3779803
6938:Bibcode
6902:3779803
6873:Bibcode
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6658:NPR.org
6631:3350522
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6572:3094067
6557:: 473.
6523:5874163
6474:3113934
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6235:2944797
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6161:Bibcode
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6074:4440916
6057:: 486.
5907:Microbe
5866:1925728
5751:3293453
5711:2127494
5652:6323928
5603:5210529
5563:4466854
5535:Bibcode
5508:4380804
5480:Bibcode
5413:2790021
5364:3053989
5341:Bibcode
5264:3526429
5213:3627586
5164:3278849
5104:Bibcode
5068:3067235
5047:Bibcode
5000:2533590
4954:bioRxiv
4930:4428112
4879:3428669
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4779:3044276
4725:3245048
4676:2563014
4659:: 386.
4625:3245063
4576:5372838
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4453:Bibcode
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4322:1800929
4257:Bibcode
4221:2896542
4172:3166839
4120:4455782
4071:2336801
4022:3488206
3973:2593568
3915:3052304
3892:Bibcode
3813:3605598
3764:3285633
3741:Bibcode
3705:4426941
3600:4010126
3545:3779803
3524:Bibcode
3469:Bibcode
3461:Science
3434:7641418
3383:5017796
3334:5830445
3313:Bibcode
3254:1465786
3202:2911387
3179:Bibcode
3143:4039370
3100:8267748
3072:Bibcode
3040:3351745
2989:1483832
2919:Bibcode
2911:Science
2866:Bibcode
2839:1454587
2801:Bibcode
2793:Science
2724:4420754
2696:Bibcode
2638:Bibcode
2611:8550487
2554:7546604
2518:2066334
2433:2413450
2401:Bibcode
2365:1185649
2342:Bibcode
2314:9818143
2264:1821061
2193:9733676
2132:2829047
2109:Bibcode
2044:Binning
1976:In the
1878:Ecology
1817:of the
1792:enzymes
1784:enzymes
1769:methane
1761:ethanol
1733:biomass
1720:Biofuel
1714:Biofuel
1708:farming
1656:ecology
1619:18S RNA
1615:16S RNA
1603:Viruses
1588:in situ
1521:methane
1394:MG-RAST
1375:ensure
1344:AMPHORA
1324:Binning
1297:GLIMMER
1241:genomes
1222:contigs
1033:vectors
1017:samples
935:species
912:archaea
860:grasses
844:cloning
816:species
713:Chimera
658:viruses
579:By taxa
563:
538:History
496:shotgun
430:genetic
399:cloning
138:History
110:Outline
7469:Fields
7395:
7354:
7344:
7297:
7287:
7246:
7236:
7224:(11).
7197:
7187:
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1947:health
1808:insect
1804:biogas
1753:sugars
1696:metals
1237:Celera
1088:, the
953:, and
947:Baltic
869:marine
746:
598:Pollen
593:Fungal
573:
524:genome
473:clonal
377:) are
324:
238:Fields
95:Allele
70:Genome
7776:(USA)
7536:Socio
7079:S2CID
6762:S2CID
6370:(PDF)
6339:(PDF)
5999:(PDF)
5992:(PDF)
5884:(PDF)
5862:S2CID
5836:arXiv
5809:S2CID
5783:arXiv
5707:S2CID
5679:(PDF)
5559:S2CID
5504:S2CID
4553:PeerJ
4419:S2CID
3861:S2CID
3493:S2CID
3417:(8).
3250:S2CID
3096:S2CID
2943:S2CID
2835:S2CID
2720:S2CID
2558:S2CID
1729:fuels
1700:crops
1668:soils
1565:(the
1413:MEGAN
1356:SLIMM
1348:mOTUs
1332:MEGAN
1328:BLAST
1283:MEGAN
1279:BLAST
1233:Phrap
1173:rumen
955:Black
627:Other
603:Algae
498:" or
115:Index
7800:List
7782:(UK)
7770:(EU)
7764:(JP)
7393:PMID
7352:PMID
7295:PMID
7244:PMID
7195:PMID
7138:PMID
7120:ISSN
7071:PMID
7063:ISSN
7024:PMID
6964:PMID
6907:PMID
6889:ISSN
6836:ISBN
6817:2011
6785:ISBN
6754:ISSN
6713:PMID
6666:2014
6636:PMID
6577:PMID
6528:PMID
6479:PMID
6428:PMID
6378:2012
6359:PMID
6312:ISBN
6289:PMID
6240:PMID
6189:PMID
6130:PMID
6079:PMID
6026:ISBN
6007:2011
5969:2011
5854:PMID
5801:PMID
5756:PMID
5699:PMID
5657:PMID
5608:PMID
5551:PMID
5496:PMID
5453:PMID
5418:PMID
5369:PMID
5310:PMID
5269:PMID
5218:PMID
5169:PMID
5122:PMID
5073:PMID
5005:PMID
4935:PMID
4884:PMID
4833:PMID
4784:PMID
4730:PMID
4681:PMID
4630:PMID
4581:PMID
4530:PMID
4479:PMID
4411:PMID
4376:PMID
4327:PMID
4275:PMID
4226:PMID
4177:PMID
4125:PMID
4076:PMID
4027:PMID
3978:PMID
3920:PMID
3853:PMID
3818:PMID
3769:PMID
3710:PMID
3661:PMID
3651:ISBN
3605:PMID
3550:PMID
3485:PMID
3439:PMID
3388:PMID
3339:PMID
3242:PMID
3207:PMID
3148:PMID
3088:PMID
3045:PMID
2994:PMID
2935:PMID
2884:PMID
2827:PMID
2774:PMID
2712:PMID
2666:PMID
2607:PMID
2550:PMID
2514:PMID
2460:ISBN
2429:PMID
2370:PMID
2310:PMID
2269:PMID
2216:ISBN
2189:PMID
2137:PMID
1899:and
1842:and
1834:and
1778:The
1771:and
1741:corn
1727:are
1702:and
1692:iron
1666:The
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