344:
208:
35:, also called miRNAs. miRNA-seq differs from other forms of RNA-seq in that input material is often enriched for small RNAs. miRNA-seq allows researchers to examine tissue-specific expression patterns, disease associations, and isoforms of miRNAs, and to discover previously uncharacterized miRNAs. Evidence that dysregulated miRNAs play a role in diseases such as
160:. However, this method is exhaustive in terms of time and resources, as each clone has to be individually amplified and prepared for sequencing. This method also inadvertently favors miRNAs that are highly expressed. Next-generation sequencing eliminates the need for sequence specific hybridization probes required in
4243:
Linsen, Sam E V; de Wit, Elzo; Janssens, Georges; Heater, Sheila; Chapman, Laura; Parkin, Rachael K; Fritz, Brian; Wyman, Stacia K; de Bruijn, Ewart; Voest, Emile E; Kuersten, Scott; Tewari, Muneesh; Cuppen, Edwin (2009). "Limitations and possibilities of small RNA digital gene expression profiling".
2495:
Cloonan, Nicole; Wani, Shivangi; Xu, Qinying; Gu, Jian; Lea, Kristi; Heater, Sheila; Barbacioru, Catalin; Steptoe, Anita L; Martin, Hilary C; Nourbakhsh, Ehsan; Krishnan, Keerthana; Gardiner, Brooke; Wang, Xiaohui; Nones, Katia; Steen, Jason A; Matigan, Nick; Wood, David L; Kassahn, Karin S; Waddell,
3291:
Keller, Andreas; Backes, Christina; Leidinger, Petra; Kefer, Nathalie; Boisguerin, Valesca; Barbacioru, Catalin; Vogel, Britta; Matzas, Mark; Huwer, Hanno; Katus, Hugo A.; Stähler, Cord; Meder, Benjamin; Meese, Eckart (2011). "Next-generation sequencing identifies novel microRNAs in peripheral blood
478:
Many miRNAs function to direct cleavage of their mRNA targets; this is particularly true in plants, and thus high-throughput sequencing methods have been developed to take advantage of this property of miRNAs by sequencing the uncapped 3' ends of cleaved or degraded mRNAs. These methods are known as
437:
After the abundances of miRNAs are quantified for each sample, their expression levels can be compared between samples. One would then be able to identify miRNA that are preferentially expressed that particular time points, or in particular tissues or disease states. After normalizing for the number
271:
Isolated RNA is run on a denaturing polyacrylamide gel. An imaging method such as radioactive 5’-32P-labeled oligonucleotides along with a size ladder is used to identify a section of the gel containing RNA of the appropriate size, reducing the amount of material ultimately sequenced. This step
4094:
Marcucci, Guido; Radmacher, Michael D.; Maharry, Kati; Mrózek, Krzysztof; Ruppert, Amy S.; Paschka, Peter; Vukosavljevic, Tamara; Whitman, Susan P.; Baldus, Claudia D.; Langer, Christian; Liu, Chang-Gong; Carroll, Andrew J.; Powell, Bayard L.; Garzon, Ramiro; Croce, Carlo M.; Kolitz, Jonathan E.;
822:
The disadvantages of using miRNA-seq over other methods of miRNA profiling are that it is more expensive, generally requires a larger amount of total RNA, involves extensive amplification, and is more time-consuming than microarray and qPCR methods. As well, miRNA-seq library preparation methods
356:
miRNAs may be preferentially expressed in certain cell types, tissues, stages of development, or in particular disease states such as cancer. Since deep sequencing (miRNA-seq) generates millions of reads from a given sample, it allows us to profile miRNAs; whether it may be by quantifying their
3736:
Ueda, Tetsuya; Volinia, Stefano; Okumura, Hiroshi; Shimizu, Masayoshi; Taccioli, Cristian; Rossi, Simona; Alder, Hansjuerg; Liu, Chang-gong; Oue, Naohide; Yasui, Wataru; Yoshida, Kazuhiro; Sasaki, Hiroki; Nomura, Sachiyo; Seto, Yasuyuki; Kaminishi, Michio; Calin, George A; Croce, Carlo M (2010).
4144:
Calin, George Adrian; Ferracin, Manuela; Cimmino, Amelia; Di Leva, Gianpiero; Shimizu, Masayoshi; Wojcik, Sylwia E.; Iorio, Marilena V.; Visone, Rosa; Sever, Nurettin Ilfer; Fabbri, Muller; Iuliano, Rodolfo; Palumbo, Tiziana; Pichiorri, Flavia; Roldo, Claudia; Garzon, Ramiro; Sevignani, Cinzia;
180:
sequencing platform. This study demonstrated the potential of novel, high-throughput sequencing technologies for the study of small RNAs, and it showed that genomes generate large numbers of small RNAs with plants as particularly rich sources of small RNAs. Later studies used other sequencing
3184:
Jima, D. D.; Zhang, J.; Jacobs, C.; Richards, K. L.; Dunphy, C. H.; Choi, W. W. L.; Yan Au, W.; Srivastava, G.; Czader, M. B.; Rizzieri, D. A.; Lagoo, A. S.; Lugar, P. L.; Mann, K. P.; Flowers, C. R.; Bernal-Mizrachi, L.; Naresh, K. N.; Evens, A. M.; Gordon, L. I.; Luftig, M.; Friedman, D. R.;
284:
amplification. An adenylated single strand DNA 3’adaptor followed by a 5’adaptor is ligated to the small RNAs using a ligating enzyme such as T4 RNA ligase2. The adaptors are also designed to capture small RNAs with a 5’ phosphate group, characteristic microRNAs, rather than RNA degradation
521:
expression. In combination with the development of high-throughput profiling methods, miRNAs have been identified as biomarkers for cancer classification, response to therapy, and prognosis. Additionally, because miRNAs regulate gene expression they can also reveal perturbations in important
450:
Identifying a miRNA's mRNA targets will provide an understanding of the genes or networks of genes whose expression they regulate. Public databases provide predictions of miRNA targets. But to better distinguish true positive predictions from false positive predictions, miRNA-seq data can be
39:
has positioned miRNA-seq to potentially become an important tool in the future for diagnostics and prognostics as costs continue to decrease. Like other miRNA profiling technologies, miRNA-Seq has both advantages (sequence-independence, coverage) and disadvantages (high cost, infrastructure
500:
miRNA-seq has revealed novel miRNAs that were previously eluded in traditional miRNA profiling methods. Examples of such findings are in embryonic stem cells, chicken embryos, acute lymphoblastic leukaemia, diffuse large b-cell lymphoma and b-cells, acute myeloid leukemia, and lung cancer.
3574:
Iorio, M. V.; Ferracin, M.; Liu, C.-G.; Veronese, A.; Spizzo, R.; Sabbioni, S.; Magri, E.; Pedriali, M.; Fabbri, M.; Campiglio, M.; Menard, S.; Palazzo, J. P.; Rosenberg, A.; Musiani, P.; Volinia, S.; Nenci, I.; Calin, G. A.; Querzoli, P.; Negrini, M.; Croce, C. M. (2005).
259:) reagent. A starting quantity of 50-100 μg total RNA, 1 g of tissue typically yields 1 mg of total RNA, is usually required for gel purification and size selection. Quality control of the RNA is also measured, for example running an RNA chip on Caliper LabChipGX (
361:) Note that given that the average length of sequence reads are longer than the average miRNA (17-25 nt), the 3’ and 5’ ends of the miRNA should be found on the same read. There are several miRNA abundance quantification algorithms. Their general steps are as follows:
4026:
Garzon, R.; Garofalo, M.; Martelli, M. P.; Briesewitz, R.; Wang, L.; Fernandez-Cymering, C.; Volinia, S.; Liu, C.-G.; Schnittger, S.; Haferlach, T.; Liso, A.; Diverio, D.; Mancini, M.; Meloni, G.; Foa, R.; Martelli, M. F.; Mecucci, C.; Croce, C. M.; Falini, B. (2008).
3854:
Fridman, Eddie; Dotan, Zohar; Barshack, Iris; David, Miriam Ben; Dov, Avital; Tabak, Sarit; Zion, Orit; Benjamin, Sima; Benjamin, Hila; Kuker, Hagit; Avivi, Camila; Rosenblatt, Kinneret; Polak-Charcon, Sylvie; Ramon, Jacob; Rosenfeld, Nitzan; Spector, Yael (2010).
2962:
German MA, Pillay M, Jeong DH, Hetawal A, Luo S, Janardhanan P, Kannan V, Rymarquis LA, Nobuta K, German R, De Paoli E, Lu C, Schroth G, Meyers BC, Green PJ (2008). "Global identification of microRNA-target RNA pairs by parallel analysis of RNA ends".
164:
analysis as well as laborious cloning methods required in the Sanger sequencing method. Additionally, next-generation sequencing platforms in the miRNA-SEQ method facilitate the sequencing of large pools of small RNAs in a single sequencing run.
339:
Central to miRNA-seq data analysis is the ability to 1) obtain miRNA abundance levels from sequence reads, 2) discover novel miRNAs and then be able to 3) determine the differentially expressed miRNA and their 4) associated mRNA gene targets.
805:
has-miR-128, has-miR-129-3p, has-miR-152, has-miR-155, has-miR-185, has-miR-193a-5p, has-miR-196b, has-miR-199b-3p, has-miR-20b, has-miR-23a, has-miR-27a, has-miR-28-5p, has-miR-301a, has-miR-331-3p, has-miR-365, has-miR-625, has-miR-9
398:
Another advantage of miRNA-seq is that it allows the discovery of novel miRNAs that may have eluded traditional screening and profiling methods. There are several novel miRNA discovery algorithms. Their general steps are as follows:
3686:
Lebanony, D.; Benjamin, H.; Gilad, S.; Ezagouri, M.; Dov, A.; Ashkenazi, K.; Gefen, N.; Izraeli, S.; Rechavi, G.; Pass, H.; Nonaka, D.; Li, J.; Spector, Y.; Rosenfeld, N.; Chajut, A.; Cohen, D.; Aharonov, R.; Mansukhani, M. (2009).
823:
seem to have systematic preferential representation of the miRNA complement, and this prevents accurate determination of miRNA abundance. At the same time, the approach is hybridization independent and therefore does not require
246:
Sequence library construction can be performed using a variety of different kits depending on the high-throughput sequencing platform being employed. However, there are several common steps for small RNA sequencing preparation.
3917:
Gutiérrez, N C; Sarasquete, M E; Misiewicz-Krzeminska, I; Delgado, M; De Las Rivas, J; Ticona, F V; Fermiñán, E; Martín-Jiménez, P; Chillón, C; Risueño, A; Hernández, J M; García-Sanz, R; González, M; San Miguel, J F (2010).
409:
For the miRNA sequences were an exact match is found, obtain the genomic sequence including ~100bp of flanking sequence on either side, and run the RNA through RNA folding software such as the Vienna package.
426:
Novel miRNA sequences are identified based on the characteristic expression pattern that they display due to DICER processing: higher expression of the mature miRNA over the star strand and loop sequences.
378:
Each of the remaining sequences are aligned against a miRNA sequence database (such as miRBase) In order to account for imperfect DICER processing, a 6nt overhang on the 3’ end, and 3nt on the 5’ end are
415:
The shortlisted sequences are trimmed down to include only the possible precursor sequence and are then refolded to ensure that the precursor was not artificially stabilized by neighbouring sequences.
3627:
Lowery, Aoife J; Miller, Nicola; Devaney, Amanda; McNeill, Roisin E; Davoren, Pamela A; Lemetre, Christophe; Benes, Vladimir; Schmidt, Sabine; Blake, Jonathon; Ball, Graham; Kerin, Michael J (2009).
297:. PCR is then carried out to amplify the pool of cDNA sequences. Primers designed with unique nucleotide tags can also be used in this step to create ID tags in pooled library multiplex sequencing.
3400:
Blenkiron, Cherie; Goldstein, Leonard D; Thorne, Natalie P; Spiteri, Inmaculada; Chin, Suet-Feung; Dunning, Mark J; Barbosa-Morais, Nuno L; Teschendorff, Andrew E; Green, Andrew R; Ellis, Ian O;
293:
This step converts the small adaptor ligated RNAs into cDNA clones used in the sequencing reaction. There are many commercial kits available that will carry out this step using some form of
3794:
Ratner, Elena S.; Tuck, David; Richter, Christine; Nallur, Sunitha; Patel, Rajeshvari M.; Schultz, Vince; Hui, Pei; Schwartz, Peter E.; Rutherford, Thomas J.; Weidhaas, Joanne B. (2010).
144:
technologies in order to find novel miRNAs and their expression profiles in a given sample. miRNA sequencing in and of itself is not a new idea, initial methods of sequencing utilized
3242:
Starczynowski, D. T.; Morin, R.; McPherson, A.; Lam, J.; Chari, R.; Wegrzyn, J.; Kuchenbauer, F.; Hirst, M.; Tohyama, K.; Humphries, R. K.; Lam, W. L.; Marra, M.; Karsan, A. (2010).
827:
sequence information. Because of this, one can obtain sequences of novel miRNAs and miRNA isoforms (isoMirs), distinguish sequentially similar miRNAs, and identify point mutations.
469:
Observe for evidence of miRNA targeting in mRNA-seq or protein expression data: where the miRNA expression is high, the gene and protein expression of its target gene should be low.
3114:
Zhang, Baohong; Zhang, Hua; Yang, Jian-Hua; Zheng, Yu-Sheng; Zhang, Peng; Chen, Xiao; Wu, Jun; Xu, Ling; Luo, Xue-Qun; Ke, Zhi-Yong; Zhou, Hui; Qu, Liang-Hu; Chen, Yue-Qin (2009).
3185:
Weinberg, J. B.; Thompson, M. A.; Gill, J. I.; Liu, Q.; How, T.; Grubor, V.; Gao, Y.; Patel, A.; Wu, H.; Zhu, J.; Blobe, G. C.; Lipsky, P. E.; Chadburn, A.; Dave, S. S. (2010).
382:
The reads that do not align to the miRNA database are then loosely aligned to miRNA precursors to detect miRNAs that might carry mutations or those that have gone through
3512:
Mattie, Michael D; Benz, Christopher C; Bowers, Jessica; Sensinger, Kelly; Wong, Linda; Scott, Gary K; Fedele, Vita; Ginzinger, David; Getts, Robert; Haqq, Chris (2006).
2186:
Morin, R. D.; O'Connor, M. D.; Griffith, M.; Kuchenbauer, F.; Delaney, A.; Prabhu, A.-L.; Zhao, Y.; McDonald, H.; Zeng, T.; Hirst, M.; Eaves, C. J.; Marra, M. A. (2008).
466:
Determine the degree of conservation of miRNA:mRNA binding pairs across species. Typically, more highly binding pairs are less likely to be false positives of prediction.
88:
transcript and downregulated LIN-14 protein expression. miRNAs are now thought to be involved in the regulation of many developmental and biological processes, including
1827:"Ultra-high throughput sequencing-based small RNA discovery and discrete statistical biomarker analysis in a collection of cervical tumours and matched controls"
418:
The resulting folded sequences are considered novel miRNAs if the miRNA sequence falls within one arm of the hairpin, and are highly conserved between species.
255:
In a given sample all the RNA is extracted and isolated using an isothiocyanate/phenol/chloroform (GITC/phenol) method or a commercial product such as Trizol (
55:(miRNAs) are a family of small ribonucleic acids, 21-25 nucleotides in length, that modulate protein expression through transcript degradation, inhibition of
2403:
Hofacker, I. L.; Fontana, W.; Stadler, P. F.; Bonhoeffer, L. S.; Tacker, M.; Schuster, P. (1994). "Fast folding and comparison of RNA secondary structures".
177:
4297:"Systematic comparison of microarray profiling, real-time PCR, and next-generation sequencing technologies for measuring differential microRNA expression"
2169:
522:
regulatory networks that may be driving a particular disorder. Several applications of miRNAs as biomarkers and predictors of disease are given below.
456:
412:
Folded sequences that lie on one arm of the miRNA hairpin and have a minimum free energy of less than ~25kcal/mol are shortlisted as putative miRNA.
1994:
Hafner, Markus; Landgraf, Pablo; Ludwig, Janos; Rice, Amanda; Ojo, Tolulope; Lin, Carolina; Holoch, Daniel; Lim, Cindy; Tuschl, Thomas (2008).
1717:
Lu, C; Tej, SS; Luo, S; Haudenschild, CD; Meyers, BC; Green, PJ (Sep 2, 2005). "Elucidation of the small RNA component of the transcriptome".
3514:"Optimized high-throughput microRNA expression profiling provides novel biomarker assessment of clinical prostate and breast cancer biopsies"
3116:"Genome-Wide Analysis of Small RNA and Novel MicroRNA Discovery in Human Acute Lymphoblastic Leukemia Based on Extensive Sequencing Approach"
1685:
3920:"Deregulation of microRNA expression in the different genetic subtypes of multiple myeloma and correlation with gene expression profiling"
2105:
365:
After sequencing, the raw sequence reads are filtered based on quality. The adaptor sequences are also trimmed off the raw sequence reads.
2243:
Berninger, Philipp; Gaidatzis, Dimos; van
Nimwegen, Erik; Zavolan, Mihaela (2008). "Computational analysis of small RNA cloning data".
280:
The ligation step adds DNA adaptors to both ends of the small RNAs, which act as primer binding sites during reverse transcription and
3463:
Sempere, L. F.; Christensen, M.; Silahtaroglu, A.; Bak, M.; Heath, C. V.; Schwartz, G.; Wells, W.; Kauppinen, S.; Cole, C. N. (2007).
1768:
Ruby, J. Graham; Jan, Calvin; Player, Christopher; Axtell, Michael J.; Lee, William; Nusbaum, Chad; Ge, Hui; Bartel, David P. (2006).
311:
The actual RNA sequencing varies significantly depending on the platform used. Three common next-generation sequencing platforms are
225:
4145:
Rassenti, Laura; Alder, Hansjuerg; Volinia, Stefano; Liu, Chang-gong; Kipps, Thomas J.; Negrini, Massimo; Croce, Carlo M. (2005).
4194:
Caramuta, Stefano; Egyházi, Suzanne; Rodolfo, Monica; Witten, Daniela; Hansson, Johan; Larsson, Catharina; Lui, Weng-Onn (2010).
484:
463:
Determine miRNA:mRNA binding pairs, complementarity between the miRNA sequences at the 3’-UTR of the mRNA sequence is identified.
2496:
Nic; Shepherd, Jill; Lee, Clarence; Ichikawa, Jeff; McKernan, Kevin; Bramlett, Kelli; Kuersten, Scott; Grimmond, Sean M (2011).
517:. Consequently, it is not unexpected that miRNAs are involved in various aspects of cancer through the regulation of onco- and
1550:
Johnston, Robert J.; Hobert, Oliver (2003). "A microRNA controlling left/right neuronal asymmetry in
Caenorhabditis elegans".
389:
The read counts for each miRNA are then normalized to the total number of mapped miRNAs to report the abundance of each miRNA.
3187:"Deep sequencing of the small RNA transcriptome of normal and malignant human B cells identifies hundreds of novel microRNAs"
1367:"Posttranscriptional regulation of the heterochronic gene lin-14 by lin-4 mediates temporal pattern formation in C. elegans"
368:
The resulting reads are then formatted into a fasta file where the copy number and sequence is recorded for each unique tag.
1672:. Methods in Molecular Biology. Vol. 822. Next-Generation MicroRNA Expression Profiling Technology. pp. 19–31.
199:
SOLiD sequencing platform has also been used to examine the prognostic value of miRNAs in detecting human breast cancer.
128:). These discoveries necessitated development of techniques able to identify and characterize miRNAs, such as miRNA-seq.
3689:"Diagnostic Assay Based on hsa-miR-205 Expression Distinguishes Squamous From Nonsquamous Non-Small-Cell Lung Carcinoma"
1668:
Aldridge, Sarah; Hadfield, James (2012). "Introduction to miRNA Profiling
Technologies and Cross-Platform Comparison".
1265:
Ambros, Victor (1989). "A hierarchy of regulatory genes controls a larva-to-adult developmental switch in C. elegans".
3739:"Relation between microRNA expression and progression and prognosis of gastric cancer: a microRNA expression analysis"
3629:"MicroRNA signatures predict oestrogen receptor, progesterone receptor and HER2/neu receptor status in breast cancer"
1001:
Sandhu, S.; Garzon, R. (2011). "Potential
Applications of MicroRNAs in Cancer Diagnosis, Prognosis, and Treatment".
2606:"Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets"
141:
137:
24:
2753:"Weak seed-pairing stability and high target-site abundance decrease the proficiency of lsy-6 and other microRNAs"
2144:
1491:
439:
281:
241:
79:
gene encoded a 22 nucleotide RNA with conserved complementary binding sites in the 3’-untranslated region of the
2557:"A pattern-based method for the identification of MicroRNA binding sites and their corresponding heteroduplexes"
2188:"Application of massively parallel sequencing to microRNA profiling and discovery in human embryonic stem cells"
272:
does not have to be necessarily carried out before the ligation and reverse transcription steps outlined below.
514:
483:
or PARE. Validation of target cleavage in specific mRNAs is typically performed using a modified version of 5'
61:
4295:
Git, A.; Dvinge, H.; Salmon-Divon, M.; Osborne, M.; Kutter, C.; Hadfield, J.; Bertone, P.; Caldas, C. (2010).
1950:
Lu, C; Meyers, BC; Green, PJ (October 2007). "Construction of small RNA cDNA libraries for deep sequencing".
4358:
112:
324:
183:
124:
71:
518:
372:
294:
260:
237:
191:. Another study comparing small RNA profiles of human cervical tumours and normal tissue, utilized the
56:
3055:
Buermans, Henk PJ; Ariyurek, Yavuz; van Ommen, Gertjan; den Dunnen, Johan T; 't Hoen, Peter AC (2010).
195:
Genome
Analyzer to identify 64 novel human miRNA genes as well as 67 differentially expressed miRNAs.
1770:"Large-Scale Sequencing Reveals 21U-RNAs and Additional MicroRNAs and Endogenous siRNAs in C. elegans"
4040:
3127:
1726:
1618:
1559:
1430:
1318:"The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14"
480:
455:, miRanda, and PicTar are software designed for this purpose. A list of prediction software is given
328:
4029:"Distinctive microRNA signature of acute myeloid leukemia bearing cytoplasmic mutated nucleophosmin"
4196:"MicroRNA Expression Profiles Associated with Mutational Status and Survival in Malignant Melanoma"
229:
157:
3976:"MicroRNA expression profiling in relation to the genetic heterogeneity of acute myeloid leukemia"
3465:"Altered MicroRNA Expression Confined to Specific Epithelial Cell Subpopulations in Breast Cancer"
3244:"Genome-wide identification of human microRNAs located in leukemia-associated genomic alterations"
4277:
2988:
2635:
2586:
2428:
2087:
1807:
1750:
1650:
1591:
1532:
1472:
1298:
1247:
1191:
1134:
1080:
510:
320:
196:
192:
168:
miRNA-seq can be performed using a variety of sequencing platforms. The first analysis of small
4147:"A MicroRNA Signature Associated with Prognosis and Progression in Chronic Lymphocytic Leukemia"
1492:"The Drosophila MicroRNA Mir-14 Suppresses Cell Death and Is Required for Normal Fat Metabolism"
1214:
He, Lin; Hannon, Gregory J. (2004). "MicroRNAs: small RNAs with a big role in gene regulation".
2109:
4334:
4316:
4269:
4261:
4225:
4217:
4176:
4168:
4126:
4118:
4076:
4058:
4005:
3997:
3949:
3941:
3894:
3876:
3833:
3815:
3776:
3758:
3718:
3710:
3668:
3650:
3606:
3598:
3553:
3535:
3494:
3486:
3445:
3427:
3406:"MicroRNA expression profiling of human breast cancer identifies new markers of tumor subtype"
3379:
3361:
3317:
3309:
3273:
3265:
3224:
3206:
3163:
3145:
3096:
3078:
3037:
2980:
2935:
2927:
2892:
2841:
2823:
2782:
2733:
2684:
2627:
2578:
2537:
2519:
2477:
2469:
2420:
2385:
2367:
2328:
2310:
2268:
2260:
2225:
2207:
2163:
2079:
2071:
2033:
2015:
1967:
1925:
1907:
1866:
1848:
1799:
1791:
1742:
1699:
1691:
1681:
1642:
1634:
1583:
1575:
1524:
1516:
1464:
1456:
1415:
1396:
1388:
1347:
1339:
1290:
1282:
1239:
1231:
1183:
1175:
1126:
1118:
1072:
1064:
1018:
983:
965:
316:
145:
438:
of mapped reads between samples, one can use a host of statistical tests (like those used in
94:
69:
screen to identify molecular elements controlling post-embryonic development of the nematode
4324:
4308:
4253:
4207:
4158:
4108:
4066:
4048:
3987:
3931:
3884:
3868:
3823:
3807:
3766:
3750:
3700:
3658:
3640:
3588:
3543:
3525:
3476:
3435:
3417:
3369:
3353:
3301:
3255:
3214:
3198:
3153:
3135:
3086:
3068:
3027:
3019:
2972:
2919:
2882:
2872:
2831:
2813:
2772:
2764:
2723:
2715:
2674:
2666:
2617:
2568:
2527:
2509:
2459:
2412:
2375:
2359:
2318:
2302:
2252:
2215:
2199:
2063:
2023:
2007:
1959:
1915:
1897:
1856:
1838:
1781:
1734:
1673:
1626:
1567:
1506:
1446:
1438:
1378:
1329:
1274:
1223:
1165:
1110:
1054:
1010:
973:
957:
106:
81:
41:
1996:"Identification of microRNAs and other small regulatory RNAs using cDNA library sequencing"
187:
which identified 18 novel miRNA genes as well as a new class of nematode small RNAs termed
172:
using miRNA-seq methods examined approximately 1.4 million small RNAs from the model plant
118:
3008:"Endogenous siRNA and miRNA targets identified by sequencing of the Arabidopsis degradome"
2653:
Grimson, A; Farh, KK; Johnston, WK; Garrett-Engele, P; Lim, LP; Bartel, DP (Jul 6, 2007).
3974:
Jongen-Lavrencic, M.; Sun, S. M.; Dijkstra, M. K.; Valk, P. J. M.; Lowenberg, B. (2008).
3401:
2498:"MicroRNAs and their isomiRs function cooperatively to target common biological pathways"
4044:
3131:
1730:
1622:
1563:
1434:
343:
4329:
4296:
4071:
4028:
3889:
3856:
3828:
3795:
3771:
3738:
3663:
3628:
3548:
3513:
3440:
3405:
3374:
3341:
3219:
3186:
3158:
3115:
3091:
3056:
3032:
3007:
2887:
2860:
2836:
2801:
2777:
2752:
2728:
2703:
2679:
2654:
2532:
2497:
2380:
2347:
2323:
2290:
2220:
2187:
2028:
1995:
1920:
1885:
1861:
1826:
978:
945:
509:
Micro RNAs are important regulators of almost all cellular processes such as survival,
312:
306:
221:
207:
161:
156:
reverse transcribed from endogenous small RNAs of 21–25 bp size selected by column and
89:
28:
3754:
1511:
1170:
1153:
4352:
1383:
1366:
1334:
1317:
1278:
1014:
403:
Obtain reads that did not align to known miRNA sequences, and map them to the genome.
2992:
2639:
2590:
2464:
2448:"miRDeep-P: a computational tool for analyzing the microRNA transcriptome in plants"
2447:
2432:
1811:
1654:
1302:
1251:
4281:
2555:
Miranda KC, Huynh T, Tay Y, Ang YS, Tam WL, Thomson AM, Lim B, Rigoutsos I (2006).
2106:"Applications - Transcriptome Sequencing : 454 Life Sciences, a Roche Company"
2091:
1754:
1595:
1536:
1476:
1195:
1138:
1098:
1084:
100:
3593:
3576:
3481:
3464:
1825:
Witten, Daniela; Tibshirani, Robert; Gu, Sam; Fire, Andrew; Lui, Weng-Onn (2010).
3992:
3975:
3357:
3260:
3243:
3202:
3140:
2923:
2670:
1609:
Lee, R. C. (2001). "An
Extensive Class of Small RNAs in Caenorhabditis elegans".
3811:
3057:"New methods for next generation sequencing based microRNA expression profiling"
2256:
2011:
1963:
1677:
383:
66:
3872:
3342:"Cancer microRNAs: From subtype profiling to predictors of response to therapy"
2751:
Garcia, DM; Baek, D; Shin, C; Bell, GW; Grimson, A; Bartel, DP (Sep 11, 2011).
2622:
2605:
2573:
2556:
2514:
1786:
1769:
451:
integrated to mRNA-seq data to observe for miRNA:mRNA functional pairs. RNA22,
3422:
3023:
2877:
2800:
Agarwal, Vikram; Bell, George W.; Nam, Jin-Wu; Bartel, David P. (2015-08-12).
1101:; Han, Jinju; Siomi, Mikiko C. (2009). "Biogenesis of small RNAs in animals".
452:
256:
233:
4320:
4265:
4221:
4172:
4122:
4062:
4001:
3945:
3880:
3857:"Accurate Molecular Classification of Renal Tumors Using MicroRNA Expression"
3819:
3762:
3714:
3705:
3688:
3654:
3602:
3539:
3490:
3431:
3365:
3313:
3269:
3210:
3149:
3082:
3073:
2931:
2859:
Agarwal, V; Subtelny, AO; Thiru, P; Ulitsky, I; Bartel, DP (4 October 2018).
2827:
2655:"MicroRNA targeting specificity in mammals: determinants beyond seed pairing"
2523:
2473:
2424:
2371:
2314:
2264:
2211:
2075:
2019:
1911:
1852:
1795:
1695:
1638:
1579:
1520:
1460:
1392:
1343:
1286:
1235:
1179:
1122:
1068:
969:
944:
Farazi, Thalia A; Spitzer, Jessica I; Morozov, Pavel; Tuschl, Thomas (2011).
814:
This is not a comprehensive list of miRNAs involved with these malignancies.
4053:
2130:
1738:
1630:
1442:
4338:
4273:
4229:
4180:
4130:
4080:
4009:
3953:
3898:
3837:
3780:
3722:
3672:
3610:
3557:
3530:
3498:
3449:
3383:
3321:
3277:
3228:
3167:
3100:
3041:
2984:
2939:
2896:
2845:
2786:
2737:
2688:
2631:
2582:
2541:
2481:
2389:
2332:
2272:
2229:
2083:
2037:
1971:
1929:
1884:
Wu, Qian; Lu, Zuhong; Li, Hailing; Lu, Jiafeng; Guo, Li; Ge, Qinyu (2011).
1870:
1843:
1803:
1746:
1703:
1646:
1587:
1528:
1468:
1243:
1187:
1130:
1076:
1022:
987:
4257:
2719:
2363:
1902:
1400:
1351:
1294:
1059:
1042:
4163:
4146:
4113:
4096:
3936:
3919:
2306:
52:
32:
4312:
4212:
4195:
4095:
Caligiuri, Michael A.; Larson, Richard A.; Bloomfield, Clara D. (2008).
2818:
1571:
3305:
2416:
2203:
1451:
371:
Sequences that may represent E. Coli contamination are identified by a
188:
149:
20:
4097:"MicroRNA Expression in Cytogenetically Normal Acute Myeloid Leukemia"
2768:
2148:
1490:
Xu, Peizhang; Vernooy, Stephanie Y.; Guo, Ming; Hay, Bruce A. (2003).
961:
550:
miR-26a/b, miR-30 family, miR-29b, miR-155, miR-342, miR-206, miR-191
1886:"Next-Generation Sequencing of MicroRNAs for Breast Cancer Detection"
358:
36:
3645:
3340:
Chan, Elcie; Prado, Daniel Estévez; Weidhaas, Joanne Barnes (2011).
2976:
2067:
2054:
Shendure, Jay; Ji, Hanlee (2008). "Next-generation DNA sequencing".
1227:
1114:
2348:"miRBase: integrating microRNA annotation and deep-sequencing data"
635:
miR-19a/b, miR-30e-5p, miR-101, miR-452, miR-382, miR-15a, miR-29c
136:
MicroRNA sequencing (miRNA-seq) was developed to take advantage of
342:
206:
3796:"MicroRNA signatures differentiate uterine cancer tumor subtypes"
2952:
Krek, A. Identification of microRNA targets. DAI-B 70/07, (2010).
2910:
Maziere, P; Enright, A (2007). "Prediction of microRNA targets".
375:
search against an E. Coli database and are removed from analysis.
178:
Lynx
Therapeutics' Massively Parallel Signature Sequencing (MPSS)
59:, or sequestering transcripts. The first miRNA to be discovered,
148:
methods. Sequencing preparation involved creating libraries by
85:
2802:"Predicting effective microRNA target sites in mammalian mRNAs"
3577:"MicroRNA Gene Expression Deregulation in Human Breast Cancer"
2702:
Friedman, RC; Farh, KK; Burge, CB; Bartel, DP (January 2009).
1316:
Lee, Rosalind C.; Feinbaum, Rhonda L.; Ambros, Victor (1993).
169:
153:
3969:
3967:
3965:
3963:
3912:
3910:
3908:
1416:"MicroRNAs Modulate Hematopoietic Lineage Differentiation"
3395:
3393:
2704:"Most mammalian mRNAs are conserved targets of microRNAs"
716:
miR-382, miR-134, miR-376a, miR-127, miR-299-5p, miR-323
357:
absolute abundance, to discover their variants (known as
2289:
Creighton, C. J.; Reid, J. G.; Gunaratne, P. H. (2009).
2181:
2179:
1670:
Next-Generation MicroRNA Expression
Profiling Technology
1154:"MicroRNAsGenomics, Biogenesis, Mechanism, and Function"
740:
miR-10a/b, let-7, miR-29, miR-204, miR-128a, miR-196a/b
319:
platform, polymerase-based sequence-by-synthesis on the
267:
2861:"Predicting microRNA targeting efficacy in Drosophila"
2291:"Expression profiling of microRNAs by deep sequencing"
4021:
4019:
3006:
Addo-Quaye C, Eshoo TW, Bartel DP, Axtell MJ (2008).
1989:
1987:
1985:
1983:
1981:
2284:
2282:
526:
Table 1: Cancer subtypes distinguished by microRNAs
3849:
3847:
3622:
3620:
939:
937:
1043:"MicroRNA profiling: separating signal from noise"
560:let-7c, miR-29b, miR-26a, miR-30 family, miR-520g
2049:
2047:
3335:
3333:
3331:
3179:
3177:
1365:Wightman, Bruce; Ha, Ilho; Ruvkun, Gary (1993).
838:Table 2: Platform Comparison of miRNA Profiling
818:Comparison With Other Methods of miRNA Profiling
574:miR-520d, miR-181c, miR-302c, miR-376b, miR-30e
4033:Proceedings of the National Academy of Sciences
2604:Lewis, BP; Burge CB; Bartel DP (Jan 14, 2005).
1945:
1943:
1941:
1939:
1209:
1207:
1205:
352:miRNA Alignment & Abundance Quantification
8:
3569:
3567:
771:miR-15a, miR-195, miR-221, miR-155, miR-23b
1036:
1034:
1032:
289:Reverse Transcription and PCR Amplification
2346:Kozomara, A.; Griffiths-Jones, S. (2010).
898:Infrastructure and technical requirements
474:Target Validation for Cleaved mRNA Targets
4328:
4211:
4162:
4112:
4070:
4052:
3991:
3935:
3888:
3827:
3770:
3704:
3662:
3644:
3592:
3547:
3529:
3480:
3439:
3421:
3373:
3259:
3218:
3157:
3139:
3090:
3072:
3031:
2886:
2876:
2835:
2817:
2776:
2757:Nature Structural & Molecular Biology
2727:
2678:
2621:
2572:
2531:
2513:
2463:
2379:
2322:
2219:
2027:
1919:
1901:
1860:
1842:
1785:
1510:
1450:
1382:
1333:
1169:
1058:
977:
3404:; Caldas, Carlos; Miska, Eric A (2007).
1890:Journal of Biomedicine and Biotechnology
836:
524:
423:Star Strand Expression Method (miRdeep)
40:requirements, run length, and potential
933:
442:) to determine differential expression
2168:: CS1 maint: archived copy as title (
2161:
831:Platform Comparison of miRNA Profiling
27:or massively parallel high-throughput
1103:Nature Reviews Molecular Cell Biology
618:miR-29b/c, miR-30 family, miR-135a/b
7:
4200:Journal of Investigative Dermatology
3861:The Journal of Molecular Diagnostics
794:
777:
760:
705:
668:
641:
624:
607:
580:
541:
285:products with a 5’ hydroxyl group.
652:miR-424, miR-203, miR-31, miR-126
632:Endometrioid vs uterine papillary
601:miR-17-5p, miR-22, miR-24, miR-31
14:
893:Five or more orders of magnitude
181:technologies, such as a study in
1015:10.1053/j.seminoncol.2011.08.007
485:Rapid Amplification of cDNA Ends
433:Differential Expression Analysis
4151:New England Journal of Medicine
4101:New England Journal of Medicine
17:MicroRNA sequencing (miRNA-seq)
802:Diffuse Large B Cell Lymphoma
768:ZAP-70 levels and IgVH status
588:Squamous vs non-squamous cell
496:Identification of Novel miRNAs
1:
3755:10.1016/S1470-2045(09)70343-2
3594:10.1158/0008-5472.CAN-05-1783
3482:10.1158/0008-5472.CAN-07-5019
2465:10.1093/bioinformatics/btr430
1512:10.1016/S0960-9822(03)00250-1
1171:10.1016/S0092-8674(04)00045-5
598:Small cell vs non-small cell
487:with a gene-specific primer.
3993:10.1182/blood-2008-01-133355
3693:Journal of Clinical Oncology
3358:10.1016/j.molmed.2011.01.008
3346:Trends in Molecular Medicine
3261:10.1182/blood-2010-03-277012
3203:10.1182/blood-2010-05-285403
3141:10.1371/journal.pone.0006849
2924:10.1016/j.drudis.2007.04.002
2671:10.1016/j.molcel.2007.06.017
1384:10.1016/0092-8674(93)90530-4
1335:10.1016/0092-8674(93)90529-Y
1279:10.1016/0092-8674(89)90171-2
762:Chronic lymphocytic leukemia
226:Phenol–chloroform extraction
116:) and neuronal development (
3812:10.1016/j.ygyno.2010.05.010
2295:Briefings in Bioinformatics
2257:10.1016/j.ymeth.2007.10.002
2012:10.1016/j.ymeth.2007.09.009
1964:10.1016/j.ymeth.2007.05.002
1678:10.1007/978-1-61779-427-8_2
788:miR-193a, miR-338, miR-565
699:miR-125a, miR-650, miR-184
4375:
3873:10.2353/jmoldx.2010.090187
3292:of lung cancer patients".
2623:10.1016/j.cell.2004.12.035
2574:10.1016/j.cell.2006.07.031
2515:10.1186/gb-2011-12-12-r126
1787:10.1016/j.cell.2006.10.040
689:miR-203, miR-155, miR-375
659:Oncocytoma vs chromophobe
304:
219:
142:high-throughput sequencing
138:next-generation sequencing
25:next-generation sequencing
3423:10.1186/gb-2007-8-10-r214
3024:10.1016/j.cub.2008.04.042
2878:10.1186/s13059-018-1504-3
2446:Yang, X.; Li, L. (2011).
911:
897:
890:Four orders of magnitude
883:
869:
855:
850:
847:
844:
842:
459:. The general steps are:
440:gene expression profiling
242:Polymerase chain reaction
211:miRNA Library Preparation
65:, was found in a genetic
3706:10.1200/JCO.2008.19.4134
3074:10.1186/1471-2164-11-716
950:The Journal of Pathology
946:"miRNAs in human cancer"
887:Six orders of magnitude
723:with t(8;21) or inv(16)
649:Clear cell vs papillary
4054:10.1073/pnas.0800135105
2358:(Database): D152–D157.
2131:"Illumina DesignStudio"
1739:10.1126/science.1114112
1631:10.1126/science.1065329
1443:10.1126/science.1091903
1216:Nature Reviews Genetics
884:Dynamic range detected
347:miRNA-seq Data Analysis
113:Drosophila melanogaster
3633:Breast Cancer Research
3531:10.1186/1476-4598-5-24
2405:Monatshefte für Chemie
2352:Nucleic Acids Research
1844:10.1186/1741-7007-8-58
912:Cost per sample (USD)
707:Acute myeloid leukemia
615:Diffuse vs intestinal
348:
325:sequencing by ligation
212:
140:or massively parallel
125:Caenorhabditis elegans
72:Caenorhabditis elegans
4258:10.1038/nmeth0709-474
2720:10.1101/gr.082701.108
1060:10.1038/nmeth0910-687
1041:Baker, Monya (2010).
662:miR-200c, miR-139-5p
519:tumor suppressor gene
394:Novel miRNA Discovery
346:
295:reverse transcriptase
261:Caliper Life Sciences
238:Reverse transcriptase
216:Small RNA Preparation
210:
104:), lipid metabolism (
4164:10.1056/NEJMoa050995
4114:10.1056/NEJMoa074256
3937:10.1038/leu.2009.274
3800:Gynecologic Oncology
3294:Molecular BioSystems
2912:Drug Discovery Today
2056:Nature Biotechnology
1414:Chen, C.-Z. (2004).
481:Degradome sequencing
329:ABI Solid Sequencing
174:Arabidopsis thaliana
4313:10.1261/rna.1947110
4213:10.1038/jid.2010.63
4045:2008PNAS..105.3945G
3743:The Lancet Oncology
3475:(24): 11612–11620.
3132:2009PLoSO...4.6849Z
2819:10.7554/eLife.05005
2364:10.1093/nar/gkq1027
1903:10.1155/2011/597145
1731:2005Sci...309.1567L
1623:2001Sci...294..862L
1572:10.1038/nature02255
1564:2003Natur.426..845J
1435:2004Sci...303...83C
870:Total RNA required
839:
527:
406:RNA Folding Method
251:Total RNA Isolation
230:Gel Electrophoresis
158:gel electrophoresis
3306:10.1039/c1mb05353a
2918:(11–12): 452–458.
2417:10.1007/BF00818163
2307:10.1093/bib/bbp019
2204:10.1101/gr.7179508
1152:Bartel, D (2004).
879:500-5,000 ng
876:100-1,000 ng
837:
726:let-7b/c, miR-127
525:
505:Disease biomarkers
349:
321:Illumina (company)
213:
197:Applied Biosystems
193:Illumina (company)
4157:(17): 1793–1801.
4107:(18): 1919–1928.
4039:(10): 3945–3950.
3986:(10): 5078–5085.
3699:(12): 2030–2037.
3587:(16): 7065–7070.
3197:(23): e118–e127.
2769:10.1038/nsmb.2115
2062:(10): 1135–1145.
1687:978-1-61779-426-1
1617:(5543): 862–864.
1558:(6968): 845–849.
962:10.1002/path.2806
925:
924:
812:
811:
446:Target Prediction
317:454 Life Sciences
146:Sanger sequencing
4366:
4343:
4342:
4332:
4292:
4286:
4285:
4240:
4234:
4233:
4215:
4206:(8): 2062–2070.
4191:
4185:
4184:
4166:
4141:
4135:
4134:
4116:
4091:
4085:
4084:
4074:
4056:
4023:
4014:
4013:
3995:
3971:
3958:
3957:
3939:
3914:
3903:
3902:
3892:
3851:
3842:
3841:
3831:
3791:
3785:
3784:
3774:
3733:
3727:
3726:
3708:
3683:
3677:
3676:
3666:
3648:
3624:
3615:
3614:
3596:
3571:
3562:
3561:
3551:
3533:
3518:Molecular Cancer
3509:
3503:
3502:
3484:
3460:
3454:
3453:
3443:
3425:
3397:
3388:
3387:
3377:
3337:
3326:
3325:
3288:
3282:
3281:
3263:
3239:
3233:
3232:
3222:
3181:
3172:
3171:
3161:
3143:
3111:
3105:
3104:
3094:
3076:
3052:
3046:
3045:
3035:
3003:
2997:
2996:
2959:
2953:
2950:
2944:
2943:
2907:
2901:
2900:
2890:
2880:
2856:
2850:
2849:
2839:
2821:
2797:
2791:
2790:
2780:
2748:
2742:
2741:
2731:
2699:
2693:
2692:
2682:
2650:
2644:
2643:
2625:
2601:
2595:
2594:
2576:
2552:
2546:
2545:
2535:
2517:
2492:
2486:
2485:
2467:
2443:
2437:
2436:
2400:
2394:
2393:
2383:
2343:
2337:
2336:
2326:
2286:
2277:
2276:
2240:
2234:
2233:
2223:
2183:
2174:
2173:
2167:
2159:
2157:
2156:
2147:. Archived from
2141:
2135:
2134:
2127:
2121:
2120:
2118:
2117:
2108:. Archived from
2102:
2096:
2095:
2051:
2042:
2041:
2031:
1991:
1976:
1975:
1947:
1934:
1933:
1923:
1905:
1881:
1875:
1874:
1864:
1846:
1822:
1816:
1815:
1789:
1780:(6): 1193–1207.
1765:
1759:
1758:
1725:(5740): 1567–9.
1714:
1708:
1707:
1665:
1659:
1658:
1606:
1600:
1599:
1547:
1541:
1540:
1514:
1496:
1487:
1481:
1480:
1454:
1420:
1411:
1405:
1404:
1386:
1362:
1356:
1355:
1337:
1313:
1307:
1306:
1262:
1256:
1255:
1211:
1200:
1199:
1173:
1149:
1143:
1142:
1095:
1089:
1088:
1062:
1038:
1027:
1026:
998:
992:
991:
981:
941:
856:Throughput time
840:
785:with BRAF V600E
679:miR-1, miR-133a
528:
23:, is the use of
4374:
4373:
4369:
4368:
4367:
4365:
4364:
4363:
4349:
4348:
4347:
4346:
4307:(5): 991–1006.
4294:
4293:
4289:
4242:
4241:
4237:
4193:
4192:
4188:
4143:
4142:
4138:
4093:
4092:
4088:
4025:
4024:
4017:
3973:
3972:
3961:
3916:
3915:
3906:
3853:
3852:
3845:
3793:
3792:
3788:
3735:
3734:
3730:
3685:
3684:
3680:
3646:10.1186/bcr2257
3626:
3625:
3618:
3581:Cancer Research
3573:
3572:
3565:
3511:
3510:
3506:
3469:Cancer Research
3462:
3461:
3457:
3399:
3398:
3391:
3339:
3338:
3329:
3300:(12): 3187–99.
3290:
3289:
3285:
3241:
3240:
3236:
3183:
3182:
3175:
3113:
3112:
3108:
3054:
3053:
3049:
3018:(10): 758–762.
3005:
3004:
3000:
2977:10.1038/nbt1417
2965:Nat. Biotechnol
2961:
2960:
2956:
2951:
2947:
2909:
2908:
2904:
2858:
2857:
2853:
2799:
2798:
2794:
2763:(10): 1139–46.
2750:
2749:
2745:
2708:Genome Research
2701:
2700:
2696:
2652:
2651:
2647:
2603:
2602:
2598:
2554:
2553:
2549:
2494:
2493:
2489:
2445:
2444:
2440:
2402:
2401:
2397:
2345:
2344:
2340:
2288:
2287:
2280:
2242:
2241:
2237:
2192:Genome Research
2185:
2184:
2177:
2160:
2154:
2152:
2145:"Archived copy"
2143:
2142:
2138:
2129:
2128:
2124:
2115:
2113:
2104:
2103:
2099:
2068:10.1038/nbt1486
2053:
2052:
2045:
1993:
1992:
1979:
1949:
1948:
1937:
1883:
1882:
1878:
1824:
1823:
1819:
1767:
1766:
1762:
1716:
1715:
1711:
1688:
1667:
1666:
1662:
1608:
1607:
1603:
1549:
1548:
1544:
1499:Current Biology
1494:
1489:
1488:
1484:
1429:(5654): 83–86.
1418:
1413:
1412:
1408:
1364:
1363:
1359:
1315:
1314:
1310:
1264:
1263:
1259:
1228:10.1038/nrg1379
1213:
1212:
1203:
1151:
1150:
1146:
1115:10.1038/nrm2632
1097:
1096:
1092:
1040:
1039:
1030:
1000:
999:
995:
943:
942:
935:
930:
833:
820:
515:differentiation
507:
498:
493:
476:
448:
435:
396:
354:
337:
309:
303:
244:
218:
205:
134:
50:
12:
11:
5:
4372:
4370:
4362:
4361:
4359:DNA sequencing
4351:
4350:
4345:
4344:
4287:
4252:(7): 474–476.
4246:Nature Methods
4235:
4186:
4136:
4086:
4015:
3959:
3930:(3): 629–637.
3904:
3867:(5): 687–696.
3843:
3806:(3): 251–257.
3786:
3749:(2): 136–146.
3728:
3678:
3616:
3563:
3504:
3455:
3410:Genome Biology
3389:
3352:(5): 235–243.
3327:
3283:
3254:(2): 595–607.
3234:
3173:
3106:
3047:
2998:
2971:(8): 941–946.
2954:
2945:
2902:
2865:Genome Biology
2851:
2792:
2743:
2694:
2659:Molecular Cell
2645:
2596:
2567:(6): 1203–17.
2547:
2502:Genome Biology
2487:
2458:(18): 2614–5.
2452:Bioinformatics
2438:
2411:(2): 167–188.
2395:
2338:
2301:(5): 490–497.
2278:
2235:
2198:(4): 610–621.
2175:
2136:
2122:
2097:
2043:
1977:
1935:
1876:
1817:
1760:
1709:
1686:
1660:
1601:
1542:
1505:(9): 790–795.
1482:
1406:
1377:(5): 855–862.
1357:
1328:(5): 843–854.
1308:
1257:
1222:(7): 522–531.
1201:
1164:(2): 281–297.
1144:
1109:(2): 126–139.
1090:
1053:(9): 687–692.
1047:Nature Methods
1028:
1009:(6): 781–787.
993:
956:(2): 102–115.
932:
931:
929:
926:
923:
922:
919:
916:
913:
909:
908:
905:
902:
899:
895:
894:
891:
888:
885:
881:
880:
877:
874:
871:
867:
866:
863:
860:
857:
853:
852:
849:
846:
843:
832:
829:
819:
816:
810:
809:
807:
803:
799:
798:
792:
791:
789:
786:
782:
781:
775:
774:
772:
769:
765:
764:
758:
757:
755:
752:
744:
743:
741:
738:
730:
729:
727:
724:
720:
719:
717:
714:
713:with t(15;17)
710:
709:
703:
702:
700:
697:
696:with t(11;14)
693:
692:
690:
687:
683:
682:
680:
677:
676:with t(14;16)
673:
672:
666:
665:
663:
660:
656:
655:
653:
650:
646:
645:
639:
638:
636:
633:
629:
628:
622:
621:
619:
616:
612:
611:
605:
604:
602:
599:
595:
594:
592:
589:
585:
584:
578:
577:
575:
572:
564:
563:
561:
558:
554:
553:
551:
548:
544:
543:
539:
538:
535:
532:
506:
503:
497:
494:
492:
489:
475:
472:
471:
470:
467:
464:
447:
444:
434:
431:
430:
429:
428:
427:
421:
420:
419:
416:
413:
410:
404:
395:
392:
391:
390:
387:
380:
376:
369:
366:
353:
350:
336:
333:
313:Pyrosequencing
307:DNA sequencing
302:
299:
222:RNA extraction
217:
214:
204:
201:
162:DNA microarray
133:
130:
90:haematopoiesis
49:
46:
29:DNA sequencing
13:
10:
9:
6:
4:
3:
2:
4371:
4360:
4357:
4356:
4354:
4340:
4336:
4331:
4326:
4322:
4318:
4314:
4310:
4306:
4302:
4298:
4291:
4288:
4283:
4279:
4275:
4271:
4267:
4263:
4259:
4255:
4251:
4247:
4239:
4236:
4231:
4227:
4223:
4219:
4214:
4209:
4205:
4201:
4197:
4190:
4187:
4182:
4178:
4174:
4170:
4165:
4160:
4156:
4152:
4148:
4140:
4137:
4132:
4128:
4124:
4120:
4115:
4110:
4106:
4102:
4098:
4090:
4087:
4082:
4078:
4073:
4068:
4064:
4060:
4055:
4050:
4046:
4042:
4038:
4034:
4030:
4022:
4020:
4016:
4011:
4007:
4003:
3999:
3994:
3989:
3985:
3981:
3977:
3970:
3968:
3966:
3964:
3960:
3955:
3951:
3947:
3943:
3938:
3933:
3929:
3925:
3921:
3913:
3911:
3909:
3905:
3900:
3896:
3891:
3886:
3882:
3878:
3874:
3870:
3866:
3862:
3858:
3850:
3848:
3844:
3839:
3835:
3830:
3825:
3821:
3817:
3813:
3809:
3805:
3801:
3797:
3790:
3787:
3782:
3778:
3773:
3768:
3764:
3760:
3756:
3752:
3748:
3744:
3740:
3732:
3729:
3724:
3720:
3716:
3712:
3707:
3702:
3698:
3694:
3690:
3682:
3679:
3674:
3670:
3665:
3660:
3656:
3652:
3647:
3642:
3638:
3634:
3630:
3623:
3621:
3617:
3612:
3608:
3604:
3600:
3595:
3590:
3586:
3582:
3578:
3570:
3568:
3564:
3559:
3555:
3550:
3545:
3541:
3537:
3532:
3527:
3523:
3519:
3515:
3508:
3505:
3500:
3496:
3492:
3488:
3483:
3478:
3474:
3470:
3466:
3459:
3456:
3451:
3447:
3442:
3437:
3433:
3429:
3424:
3419:
3415:
3411:
3407:
3403:
3402:Tavaré, Simon
3396:
3394:
3390:
3385:
3381:
3376:
3371:
3367:
3363:
3359:
3355:
3351:
3347:
3343:
3336:
3334:
3332:
3328:
3323:
3319:
3315:
3311:
3307:
3303:
3299:
3295:
3287:
3284:
3279:
3275:
3271:
3267:
3262:
3257:
3253:
3249:
3245:
3238:
3235:
3230:
3226:
3221:
3216:
3212:
3208:
3204:
3200:
3196:
3192:
3188:
3180:
3178:
3174:
3169:
3165:
3160:
3155:
3151:
3147:
3142:
3137:
3133:
3129:
3125:
3121:
3117:
3110:
3107:
3102:
3098:
3093:
3088:
3084:
3080:
3075:
3070:
3066:
3062:
3058:
3051:
3048:
3043:
3039:
3034:
3029:
3025:
3021:
3017:
3013:
3009:
3002:
2999:
2994:
2990:
2986:
2982:
2978:
2974:
2970:
2966:
2958:
2955:
2949:
2946:
2941:
2937:
2933:
2929:
2925:
2921:
2917:
2913:
2906:
2903:
2898:
2894:
2889:
2884:
2879:
2874:
2870:
2866:
2862:
2855:
2852:
2847:
2843:
2838:
2833:
2829:
2825:
2820:
2815:
2811:
2807:
2803:
2796:
2793:
2788:
2784:
2779:
2774:
2770:
2766:
2762:
2758:
2754:
2747:
2744:
2739:
2735:
2730:
2725:
2721:
2717:
2714:(1): 92–105.
2713:
2709:
2705:
2698:
2695:
2690:
2686:
2681:
2676:
2672:
2668:
2665:(1): 91–105.
2664:
2660:
2656:
2649:
2646:
2641:
2637:
2633:
2629:
2624:
2619:
2615:
2611:
2607:
2600:
2597:
2592:
2588:
2584:
2580:
2575:
2570:
2566:
2562:
2558:
2551:
2548:
2543:
2539:
2534:
2529:
2525:
2521:
2516:
2511:
2507:
2503:
2499:
2491:
2488:
2483:
2479:
2475:
2471:
2466:
2461:
2457:
2453:
2449:
2442:
2439:
2434:
2430:
2426:
2422:
2418:
2414:
2410:
2406:
2399:
2396:
2391:
2387:
2382:
2377:
2373:
2369:
2365:
2361:
2357:
2353:
2349:
2342:
2339:
2334:
2330:
2325:
2320:
2316:
2312:
2308:
2304:
2300:
2296:
2292:
2285:
2283:
2279:
2274:
2270:
2266:
2262:
2258:
2254:
2250:
2246:
2239:
2236:
2231:
2227:
2222:
2217:
2213:
2209:
2205:
2201:
2197:
2193:
2189:
2182:
2180:
2176:
2171:
2165:
2151:on 2008-05-16
2150:
2146:
2140:
2137:
2132:
2126:
2123:
2112:on 2011-05-26
2111:
2107:
2101:
2098:
2093:
2089:
2085:
2081:
2077:
2073:
2069:
2065:
2061:
2057:
2050:
2048:
2044:
2039:
2035:
2030:
2025:
2021:
2017:
2013:
2009:
2005:
2001:
1997:
1990:
1988:
1986:
1984:
1982:
1978:
1973:
1969:
1965:
1961:
1957:
1953:
1946:
1944:
1942:
1940:
1936:
1931:
1927:
1922:
1917:
1913:
1909:
1904:
1899:
1895:
1891:
1887:
1880:
1877:
1872:
1868:
1863:
1858:
1854:
1850:
1845:
1840:
1836:
1832:
1828:
1821:
1818:
1813:
1809:
1805:
1801:
1797:
1793:
1788:
1783:
1779:
1775:
1771:
1764:
1761:
1756:
1752:
1748:
1744:
1740:
1736:
1732:
1728:
1724:
1720:
1713:
1710:
1705:
1701:
1697:
1693:
1689:
1683:
1679:
1675:
1671:
1664:
1661:
1656:
1652:
1648:
1644:
1640:
1636:
1632:
1628:
1624:
1620:
1616:
1612:
1605:
1602:
1597:
1593:
1589:
1585:
1581:
1577:
1573:
1569:
1565:
1561:
1557:
1553:
1546:
1543:
1538:
1534:
1530:
1526:
1522:
1518:
1513:
1508:
1504:
1500:
1493:
1486:
1483:
1478:
1474:
1470:
1466:
1462:
1458:
1453:
1448:
1444:
1440:
1436:
1432:
1428:
1424:
1417:
1410:
1407:
1402:
1398:
1394:
1390:
1385:
1380:
1376:
1372:
1368:
1361:
1358:
1353:
1349:
1345:
1341:
1336:
1331:
1327:
1323:
1319:
1312:
1309:
1304:
1300:
1296:
1292:
1288:
1284:
1280:
1276:
1272:
1268:
1261:
1258:
1253:
1249:
1245:
1241:
1237:
1233:
1229:
1225:
1221:
1217:
1210:
1208:
1206:
1202:
1197:
1193:
1189:
1185:
1181:
1177:
1172:
1167:
1163:
1159:
1155:
1148:
1145:
1140:
1136:
1132:
1128:
1124:
1120:
1116:
1112:
1108:
1104:
1100:
1099:Kim, V. Narry
1094:
1091:
1086:
1082:
1078:
1074:
1070:
1066:
1061:
1056:
1052:
1048:
1044:
1037:
1035:
1033:
1029:
1024:
1020:
1016:
1012:
1008:
1004:
997:
994:
989:
985:
980:
975:
971:
967:
963:
959:
955:
951:
947:
940:
938:
934:
927:
920:
917:
914:
910:
906:
903:
900:
896:
892:
889:
886:
882:
878:
875:
872:
868:
864:
861:
858:
854:
841:
835:
830:
828:
826:
817:
815:
808:
804:
801:
800:
797:
793:
790:
787:
784:
783:
780:
776:
773:
770:
767:
766:
763:
759:
756:
753:
750:
746:
745:
742:
739:
736:
732:
731:
728:
725:
722:
721:
718:
715:
712:
711:
708:
704:
701:
698:
695:
694:
691:
688:
686:with t(4;14)
685:
684:
681:
678:
675:
674:
671:
667:
664:
661:
658:
657:
654:
651:
648:
647:
644:
640:
637:
634:
631:
630:
627:
623:
620:
617:
614:
613:
610:
606:
603:
600:
597:
596:
593:
590:
587:
586:
583:
579:
576:
573:
570:
566:
565:
562:
559:
556:
555:
552:
549:
546:
545:
540:
536:
533:
530:
529:
523:
520:
516:
512:
511:proliferation
504:
502:
495:
490:
488:
486:
482:
473:
468:
465:
462:
461:
460:
458:
454:
445:
443:
441:
432:
425:
424:
422:
417:
414:
411:
408:
407:
405:
402:
401:
400:
393:
388:
385:
381:
377:
374:
370:
367:
364:
363:
362:
360:
351:
345:
341:
335:Data Analysis
334:
332:
330:
326:
323:platform, or
322:
318:
314:
308:
300:
298:
296:
291:
290:
286:
283:
278:
277:
273:
269:
268:
264:
262:
258:
253:
252:
248:
243:
239:
235:
231:
227:
223:
215:
209:
202:
200:
198:
194:
190:
186:
185:
179:
175:
171:
166:
163:
159:
155:
151:
147:
143:
139:
131:
129:
127:
126:
121:
120:
115:
114:
109:
108:
103:
102:
97:
96:
91:
87:
84:
83:
78:
74:
73:
68:
64:
63:
58:
54:
47:
45:
43:
38:
34:
30:
26:
22:
18:
4304:
4300:
4290:
4249:
4245:
4238:
4203:
4199:
4189:
4154:
4150:
4139:
4104:
4100:
4089:
4036:
4032:
3983:
3979:
3927:
3923:
3864:
3860:
3803:
3799:
3789:
3746:
3742:
3731:
3696:
3692:
3681:
3636:
3632:
3584:
3580:
3521:
3517:
3507:
3472:
3468:
3458:
3416:(10): R214.
3413:
3409:
3349:
3345:
3297:
3293:
3286:
3251:
3247:
3237:
3194:
3190:
3126:(9): e6849.
3123:
3119:
3109:
3064:
3061:BMC Genomics
3060:
3050:
3015:
3011:
3001:
2968:
2964:
2957:
2948:
2915:
2911:
2905:
2868:
2864:
2854:
2809:
2805:
2795:
2760:
2756:
2746:
2711:
2707:
2697:
2662:
2658:
2648:
2616:(1): 15–20.
2613:
2609:
2599:
2564:
2560:
2550:
2508:(12): R126.
2505:
2501:
2490:
2455:
2451:
2441:
2408:
2404:
2398:
2355:
2351:
2341:
2298:
2294:
2251:(1): 13–21.
2248:
2244:
2238:
2195:
2191:
2153:. Retrieved
2149:the original
2139:
2125:
2114:. Retrieved
2110:the original
2100:
2059:
2055:
2003:
1999:
1958:(2): 110–7.
1955:
1951:
1893:
1889:
1879:
1834:
1830:
1820:
1777:
1773:
1763:
1722:
1718:
1712:
1669:
1663:
1614:
1610:
1604:
1555:
1551:
1545:
1502:
1498:
1485:
1426:
1422:
1409:
1374:
1370:
1360:
1325:
1321:
1311:
1273:(1): 49–57.
1270:
1266:
1260:
1219:
1215:
1161:
1157:
1147:
1106:
1102:
1093:
1050:
1046:
1006:
1002:
996:
953:
949:
921:$ 500–$ 700
918:$ 250–$ 350
907:Substantial
873:500 ng
834:
824:
821:
813:
795:
778:
761:
748:
734:
706:
669:
642:
625:
608:
581:
568:
508:
499:
491:Applications
477:
449:
436:
397:
355:
338:
310:
292:
288:
287:
279:
275:
274:
270:
266:
265:
254:
250:
249:
245:
182:
173:
167:
135:
123:
117:
111:
105:
101:Mus musculus
99:
93:
80:
76:
70:
60:
51:
48:Introduction
31:to sequence
19:, a type of
16:
15:
2006:(1): 3–12.
1831:BMC Biology
1452:1721.1/7483
1003:Semin Oncol
851:Sequencing
848:Microarray
626:Endometrial
531:Cancer type
384:RNA editing
67:mutagenesis
57:translation
3639:(3): R27.
3067:(1): 716.
3012:Curr. Biol
2871:(1): 152.
2812:: e05005.
2155:2008-05-16
2116:2012-03-01
928:References
865:1–2 weeks
737:mutations
557:PR status
547:ER Status
453:TargetScan
331:platform.
305:See also:
301:Sequencing
257:Invitrogen
234:DNA ligase
220:See also:
184:C. elegans
4321:1355-8382
4266:1548-7091
4222:0022-202X
4173:0028-4793
4123:0028-4793
4063:0027-8424
4002:0006-4971
3946:0887-6924
3881:1525-1578
3820:0090-8258
3763:1470-2045
3715:0732-183X
3655:1465-5411
3603:0008-5472
3540:1476-4598
3524:(1): 24.
3491:0008-5472
3432:1465-6906
3366:1471-4914
3314:1742-206X
3270:0006-4971
3211:0006-4971
3150:1932-6203
3083:1471-2164
2932:1359-6446
2828:2050-084X
2524:1465-6906
2474:1367-4803
2425:0026-9247
2372:0305-1048
2315:1467-5463
2265:1046-2023
2212:1088-9051
2076:1087-0156
2020:1046-2023
1912:1110-7243
1853:1741-7007
1837:(1): 58.
1796:0092-8674
1696:1064-3745
1639:0036-8075
1580:0028-0836
1521:0960-9822
1461:0036-8075
1393:0092-8674
1344:0092-8674
1287:0092-8674
1236:1471-0056
1180:0092-8674
1123:1471-0072
1069:1548-7091
970:0022-3417
904:Moderate
859:~6 hours
53:MicroRNAs
42:artifacts
33:microRNAs
4353:Category
4339:20360395
4274:19564845
4230:20357817
4181:16251535
4131:18450603
4081:18308931
4010:18337557
3954:20054351
3924:Leukemia
3899:20595629
3838:20542546
3781:20022810
3723:19273703
3673:19432961
3611:16103053
3558:16784538
3499:18089790
3450:17922911
3384:21354374
3322:22027949
3278:20962326
3229:20733160
3168:19724645
3120:PLOS ONE
3101:21171994
3042:18472421
2993:13187064
2985:18542052
2940:17532529
2897:30286781
2846:26267216
2787:21909094
2738:18955434
2689:17612493
2640:17316349
2632:15652477
2591:12749133
2583:16990141
2542:22208850
2482:21775303
2433:19344304
2390:21037258
2333:19332473
2273:18158128
2230:18285502
2164:cite web
2084:18846087
2038:18158127
1972:17889797
1930:21716661
1871:20459774
1812:16838469
1804:17174894
1747:16141074
1704:22144189
1655:33480585
1647:11679672
1588:14685240
1529:12725740
1469:14657504
1303:13103224
1252:86602746
1244:15211354
1188:14744438
1131:19165215
1077:20805796
1023:22082764
988:21125669
862:~2 days
825:a priori
796:Lymphoma
779:Melanoma
754:miR-155
591:miR-205
379:allowed.
276:Ligation
189:21U-RNAs
4330:2856892
4282:7953265
4072:2268779
4041:Bibcode
3890:2928434
3829:2918705
3772:4299826
3664:2716495
3549:1563474
3441:2246288
3375:3092835
3220:3012600
3159:2731166
3128:Bibcode
3092:3022920
3033:2583427
2888:6172730
2837:4532895
2778:3190056
2729:2612969
2680:3800283
2533:3334621
2381:3013655
2324:2733187
2245:Methods
2221:2279248
2092:6384349
2029:2847350
2000:Methods
1952:Methods
1921:3118289
1896:: 1–7.
1862:2880020
1755:1651848
1727:Bibcode
1719:Science
1619:Bibcode
1611:Science
1596:4410288
1560:Bibcode
1537:6391484
1477:7044929
1431:Bibcode
1423:Science
1401:8252622
1352:8252621
1295:2702689
1196:2669459
1139:8360619
1085:6853222
979:3069496
670:Myeloma
609:Gastric
571:status
542:Breast
534:miRNAs
359:isomirs
327:on the
315:on the
203:Methods
150:cloning
132:History
95:miR-181
21:RNA-Seq
4337:
4327:
4319:
4280:
4272:
4264:
4228:
4220:
4179:
4171:
4129:
4121:
4079:
4069:
4061:
4008:
4000:
3952:
3944:
3897:
3887:
3879:
3836:
3826:
3818:
3779:
3769:
3761:
3721:
3713:
3671:
3661:
3653:
3609:
3601:
3556:
3546:
3538:
3497:
3489:
3448:
3438:
3430:
3382:
3372:
3364:
3320:
3312:
3276:
3268:
3227:
3217:
3209:
3166:
3156:
3148:
3099:
3089:
3081:
3040:
3030:
2991:
2983:
2938:
2930:
2895:
2885:
2844:
2834:
2826:
2785:
2775:
2736:
2726:
2687:
2677:
2638:
2630:
2589:
2581:
2540:
2530:
2522:
2480:
2472:
2431:
2423:
2388:
2378:
2370:
2331:
2321:
2313:
2271:
2263:
2228:
2218:
2210:
2090:
2082:
2074:
2036:
2026:
2018:
1970:
1928:
1918:
1910:
1869:
1859:
1851:
1810:
1802:
1794:
1753:
1745:
1702:
1694:
1684:
1653:
1645:
1637:
1594:
1586:
1578:
1552:Nature
1535:
1527:
1519:
1475:
1467:
1459:
1399:
1391:
1350:
1342:
1301:
1293:
1285:
1250:
1242:
1234:
1194:
1186:
1178:
1137:
1129:
1121:
1083:
1075:
1067:
1021:
986:
976:
968:
915:$ 400
513:, and
240:, and
176:using
107:miR-14
82:lin-14
75:. The
37:cancer
4278:S2CID
3980:Blood
3248:Blood
3191:Blood
2989:S2CID
2806:eLife
2636:S2CID
2587:S2CID
2429:S2CID
2088:S2CID
1808:S2CID
1751:S2CID
1651:S2CID
1592:S2CID
1533:S2CID
1495:(PDF)
1473:S2CID
1419:(PDF)
1299:S2CID
1248:S2CID
1192:S2CID
1135:S2CID
1081:S2CID
845:qPCR
747:with
733:with
643:Renal
567:HER2/
537:Ref.
373:BLAST
119:lsy-6
77:lin-4
62:lin-4
4335:PMID
4317:ISSN
4270:PMID
4262:ISSN
4226:PMID
4218:ISSN
4177:PMID
4169:ISSN
4127:PMID
4119:ISSN
4077:PMID
4059:ISSN
4006:PMID
3998:ISSN
3950:PMID
3942:ISSN
3895:PMID
3877:ISSN
3834:PMID
3816:ISSN
3777:PMID
3759:ISSN
3719:PMID
3711:ISSN
3669:PMID
3651:ISSN
3607:PMID
3599:ISSN
3554:PMID
3536:ISSN
3495:PMID
3487:ISSN
3446:PMID
3428:ISSN
3380:PMID
3362:ISSN
3318:PMID
3310:ISSN
3274:PMID
3266:ISSN
3225:PMID
3207:ISSN
3164:PMID
3146:ISSN
3097:PMID
3079:ISSN
3038:PMID
2981:PMID
2936:PMID
2928:ISSN
2893:PMID
2842:PMID
2824:ISSN
2783:PMID
2734:PMID
2685:PMID
2628:PMID
2610:Cell
2579:PMID
2561:Cell
2538:PMID
2520:ISSN
2478:PMID
2470:ISSN
2421:ISSN
2386:PMID
2368:ISSN
2329:PMID
2311:ISSN
2269:PMID
2261:ISSN
2226:PMID
2208:ISSN
2170:link
2080:PMID
2072:ISSN
2034:PMID
2016:ISSN
1968:PMID
1926:PMID
1908:ISSN
1894:2011
1867:PMID
1849:ISSN
1800:PMID
1792:ISSN
1774:Cell
1743:PMID
1700:PMID
1692:ISSN
1682:ISBN
1643:PMID
1635:ISSN
1584:PMID
1576:ISSN
1525:PMID
1517:ISSN
1465:PMID
1457:ISSN
1397:PMID
1389:ISSN
1371:Cell
1348:PMID
1340:ISSN
1322:Cell
1291:PMID
1283:ISSN
1267:Cell
1240:PMID
1232:ISSN
1184:PMID
1176:ISSN
1158:Cell
1127:PMID
1119:ISSN
1073:PMID
1065:ISSN
1019:PMID
984:PMID
966:ISSN
901:Few
751:ITD
749:FLT3
735:NPM1
582:Lung
457:here
170:RNAs
86:mRNA
4325:PMC
4309:doi
4301:RNA
4254:doi
4208:doi
4204:130
4159:doi
4155:353
4109:doi
4105:358
4067:PMC
4049:doi
4037:105
3988:doi
3984:111
3932:doi
3885:PMC
3869:doi
3824:PMC
3808:doi
3804:118
3767:PMC
3751:doi
3701:doi
3659:PMC
3641:doi
3589:doi
3544:PMC
3526:doi
3477:doi
3436:PMC
3418:doi
3370:PMC
3354:doi
3302:doi
3256:doi
3252:117
3215:PMC
3199:doi
3195:116
3154:PMC
3136:doi
3087:PMC
3069:doi
3028:PMC
3020:doi
2973:doi
2920:doi
2883:PMC
2873:doi
2832:PMC
2814:doi
2773:PMC
2765:doi
2724:PMC
2716:doi
2675:PMC
2667:doi
2618:doi
2614:120
2569:doi
2565:126
2528:PMC
2510:doi
2460:doi
2413:doi
2409:125
2376:PMC
2360:doi
2319:PMC
2303:doi
2253:doi
2216:PMC
2200:doi
2064:doi
2024:PMC
2008:doi
1960:doi
1916:PMC
1898:doi
1857:PMC
1839:doi
1782:doi
1778:127
1735:doi
1723:309
1674:doi
1627:doi
1615:294
1568:doi
1556:426
1507:doi
1447:hdl
1439:doi
1427:303
1379:doi
1330:doi
1275:doi
1224:doi
1166:doi
1162:116
1111:doi
1055:doi
1011:doi
974:PMC
958:doi
954:223
569:neu
282:PCR
263:).
154:DNA
152:of
122:in
110:in
98:in
44:).
4355::
4333:.
4323:.
4315:.
4305:16
4303:.
4299:.
4276:.
4268:.
4260:.
4248:.
4224:.
4216:.
4202:.
4198:.
4175:.
4167:.
4153:.
4149:.
4125:.
4117:.
4103:.
4099:.
4075:.
4065:.
4057:.
4047:.
4035:.
4031:.
4018:^
4004:.
3996:.
3982:.
3978:.
3962:^
3948:.
3940:.
3928:24
3926:.
3922:.
3907:^
3893:.
3883:.
3875:.
3865:12
3863:.
3859:.
3846:^
3832:.
3822:.
3814:.
3802:.
3798:.
3775:.
3765:.
3757:.
3747:11
3745:.
3741:.
3717:.
3709:.
3697:27
3695:.
3691:.
3667:.
3657:.
3649:.
3637:11
3635:.
3631:.
3619:^
3605:.
3597:.
3585:65
3583:.
3579:.
3566:^
3552:.
3542:.
3534:.
3520:.
3516:.
3493:.
3485:.
3473:67
3471:.
3467:.
3444:.
3434:.
3426:.
3412:.
3408:.
3392:^
3378:.
3368:.
3360:.
3350:17
3348:.
3344:.
3330:^
3316:.
3308:.
3296:.
3272:.
3264:.
3250:.
3246:.
3223:.
3213:.
3205:.
3193:.
3189:.
3176:^
3162:.
3152:.
3144:.
3134:.
3122:.
3118:.
3095:.
3085:.
3077:.
3065:11
3063:.
3059:.
3036:.
3026:.
3016:18
3014:.
3010:.
2987:.
2979:.
2969:26
2967:.
2934:.
2926:.
2916:12
2914:.
2891:.
2881:.
2869:19
2867:.
2863:.
2840:.
2830:.
2822:.
2808:.
2804:.
2781:.
2771:.
2761:18
2759:.
2755:.
2732:.
2722:.
2712:19
2710:.
2706:.
2683:.
2673:.
2663:27
2661:.
2657:.
2634:.
2626:.
2612:.
2608:.
2585:.
2577:.
2563:.
2559:.
2536:.
2526:.
2518:.
2506:12
2504:.
2500:.
2476:.
2468:.
2456:27
2454:.
2450:.
2427:.
2419:.
2407:.
2384:.
2374:.
2366:.
2356:39
2354:.
2350:.
2327:.
2317:.
2309:.
2299:10
2297:.
2293:.
2281:^
2267:.
2259:.
2249:44
2247:.
2224:.
2214:.
2206:.
2196:18
2194:.
2190:.
2178:^
2166:}}
2162:{{
2086:.
2078:.
2070:.
2060:26
2058:.
2046:^
2032:.
2022:.
2014:.
2004:44
2002:.
1998:.
1980:^
1966:.
1956:43
1954:.
1938:^
1924:.
1914:.
1906:.
1892:.
1888:.
1865:.
1855:.
1847:.
1833:.
1829:.
1806:.
1798:.
1790:.
1776:.
1772:.
1749:.
1741:.
1733:.
1721:.
1698:.
1690:.
1680:.
1649:.
1641:.
1633:.
1625:.
1613:.
1590:.
1582:.
1574:.
1566:.
1554:.
1531:.
1523:.
1515:.
1503:13
1501:.
1497:.
1471:.
1463:.
1455:.
1445:.
1437:.
1425:.
1421:.
1395:.
1387:.
1375:75
1373:.
1369:.
1346:.
1338:.
1326:75
1324:.
1320:.
1297:.
1289:.
1281:.
1271:57
1269:.
1246:.
1238:.
1230:.
1218:.
1204:^
1190:.
1182:.
1174:.
1160:.
1156:.
1133:.
1125:.
1117:.
1107:10
1105:.
1079:.
1071:.
1063:.
1049:.
1045:.
1031:^
1017:.
1007:38
1005:.
982:.
972:.
964:.
952:.
948:.
936:^
236:,
232:,
228:,
224:,
4341:.
4311::
4284:.
4256::
4250:6
4232:.
4210::
4183:.
4161::
4133:.
4111::
4083:.
4051::
4043::
4012:.
3990::
3956:.
3934::
3901:.
3871::
3840:.
3810::
3783:.
3753::
3725:.
3703::
3675:.
3643::
3613:.
3591::
3560:.
3528::
3522:5
3501:.
3479::
3452:.
3420::
3414:8
3386:.
3356::
3324:.
3304::
3298:7
3280:.
3258::
3231:.
3201::
3170:.
3138::
3130::
3124:4
3103:.
3071::
3044:.
3022::
2995:.
2975::
2942:.
2922::
2899:.
2875::
2848:.
2816::
2810:4
2789:.
2767::
2740:.
2718::
2691:.
2669::
2642:.
2620::
2593:.
2571::
2544:.
2512::
2484:.
2462::
2435:.
2415::
2392:.
2362::
2335:.
2305::
2275:.
2255::
2232:.
2202::
2172:)
2158:.
2133:.
2119:.
2094:.
2066::
2040:.
2010::
1974:.
1962::
1932:.
1900::
1873:.
1841::
1835:8
1814:.
1784::
1757:.
1737::
1729::
1706:.
1676::
1657:.
1629::
1621::
1598:.
1570::
1562::
1539:.
1509::
1479:.
1449::
1441::
1433::
1403:.
1381::
1354:.
1332::
1305:.
1277::
1254:.
1226::
1220:5
1198:.
1168::
1141:.
1113::
1087:.
1057::
1051:7
1025:.
1013::
990:.
960::
386:.
92:(
Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.