431:
In addition, a web meta-server named PLAtform of TOols for LOw COmplexity (PlaToLoCo) has been developed, for visualization and annotation of low complexity regions in proteins. PlaToLoCo integrates and collects the output of five different state-of-the-art tools for discovering LCRs and provides
374:
A web platform to search, visualize and share data for low complexity regions in protein sequences. LCR-eXXXplorer offers tools for displaying LCRs from the UniProt/SwissProt knowledgebase, in combination with other relevant protein features, predicted or experimentally verified. Also, users may
350:
This algorithm defines compositional bias through a thorough search for lowest-probability subsequences (LPSs; Low
Probability Sequences) and serves as workbench of tools now available to molecular biologists to generate hypotheses and inferences about the proteins that they are investigating.
432:
functional annotations such as domain detection, transmembrane segment prediction, and calculation of amino acid frequencies. Furthermore, the union or intersection of the results of the search on a query sequence can be obtained.
113:
It can readily handle very large protein data sets, such as might come from metagenomics projects. It is useful in searching for proteins with similar CBRs and for making functional inferences about CBRs for a protein of interest
266:
It uses discrete scan statistics that provide a highly accurate multiple test correction to compute analytical estimates of the significance of each compositionally biased segment.
747:
Nandi T, Dash D, Ghai R, B-Rao C, Kannan K, Brahmachari SK, Ramakrishnan C, Ramachandran S (2003). "A new algorithm for detecting low-complexity regions in protein sequences".
435:
A Neural
Network webserver, named LCR-hound has been developed to predict the function of prokaryotic and eukaryotic LCRs, based on their amino acid or di-amino acid content.
163:
It facilitates the quantification of the amount of simple sequence in proteins and determines the type of short motifs that show clustering above a certain threshold.
65:
It describes several protein sequence statistics for the evaluation of distinctive characteristics of residue content and arrangement in primary structures.
1242:
Jarnot P, Ziemska-Legiecka J, Dobson L, Merski M, Mier P, Andrade-Navarro MA, Hancock JM, Dosztányi Z, Paladin L, Necci M, Piovesan D (2020-07-02).
1185:
Mier P, Paladin L, Tamana S, Petrosian S, Hajdu-Soltész B, Urbanek A, Gruca A, Plewczynski D, Grynberg M, Bernadó P, Gáspári Z (2020-03-23).
19:
954:
Ooi HS, Kwo CY, Wildpaner M, Sirota FL, Eisenhaber B, Maurer-Stroh S, Wong WC, Schleiffer A, Eisenhaber F, Schneider G (Jul 2009).
712:
Wan H, Li L, Federhen S, Wootton JC (2003). "Discovering simple regions in biological sequences associated with scoring schemes".
1299:
Ntountoumi C, Vlastaridis P, Mossialos D, Stathopoulos C, Iliopoulos I, Promponas V, Oliver SG, Amoutzias GD (2019-11-04).
915:"SubSeqer: a graph-based approach for the detection and identification of repetitive elements in low-complexity sequences"
86:
It is a two pass algorithm: first, identifies the LCR, and then performs local optimization by masking with Xs the LCRs
591:"CAST: an iterative algorithm for the complexity analysis of sequence tracts. Complexity analysis of sequence tracts"
511:
Wootton JC, Federhen S (June 2003). "Statistics of local complexity in amino acid sequences and sequence databases".
1054:"LCR-eXXXplorer: a web platform to search, visualize and share data for low complexity regions in protein sequences"
1367:
1301:"Low complexity regions in the proteins of prokaryotes perform important functional roles and are highly conserved"
308:
A graph-based approach for the detection and identification of repetitive elements in low–complexity sequences.
1244:"PlaToLoCo: the first web meta-server for visualization and annotation of low complexity regions in proteins"
1130:"AlcoR: alignment-free simulation, mapping, and visualization of low-complexity regions in biological data"
239:
Based on the complexity analysis of subsequences delimited by pairs of identical, repeating subsequences.
1101:
Claverie JM, States D (June 1993). "Information enhancement methods for large scale sequence analysis".
833:"A novel sensitive method for the detection of user-defined compositional bias in biological sequences"
589:
Promponas VJ, Enright AJ, Tsoka S, Kreil DP, Leroy C, Hamodrakas S, Sander C, Ouzounis CA (Oct 2000).
465:
417:
A compression-based and alignment-free tool for detecting low-complexity regions in biological data
1362:
1005:"LPS-annotate: complete annotation of compositionally biased regions in the protein knowledgebase"
772:
792:"A novel complexity measure for comparative analysis of protein sequences from complete genomes"
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220:
Calculates the compositional complexity using the linguistic complexity measure.
874:"A Novel algorithm for identifying low-complexity regions in a protein sequence"
725:
22:, which can have particular properties regarding their function and structure.
1129:
1020:
556:
1324:
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1228:
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989:
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768:
733:
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632:"Detecting cryptically simple protein sequences using the SIMPLE algorithm"
616:
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478:
391:
18:
Computational methods can study protein sequences to identify regions with
1259:
497:
452:
Brendel V, Bucher P, Nourbakhsh IR, Blaisdell BE, Karlin S (15 Mar 1992).
158:
147:
1316:
1202:
971:
375:
perform queries against a custom designed sequence/LCR-centric database.
673:"0j.py: a software tool for low complexity proteins and protein domains"
540:"fLPS: Fast discovery of compositional biases for the protein universe"
81:
454:"Methods and algorithms for statistical analysis of protein sequences"
396:
It uses the PAM120 scoring matrix for the calculation of complexity.
261:
249:
104:
331:
This method creates an automation of the sequence analytic process.
412:
428:
For a comprehensive review on the various methods and tools, see.
303:
295:
257:
326:
318:
285:
A graph-based algorithm that constructs a graph of the sequence.
1187:"Disentangling the complexity of low complexity proteins"
956:"ANNIE: integrated de novo protein sequence annotation"
182:
A tool for demarcating low complexity protein domains.
201:
It calculates complexity using reciprocal complexity.
1128:Silva JM, Qi W, Pinho AJ, Pratas D (2022-12-28).
630:Albà MM, Laskowski RA, Hancock JM (May 2002).
137:It identifies LCRs using dynamic programming.
8:
1003:Harbi D, Kumar M, Harrison PM (6 Jan 2011).
1052:Kirmitzoglou I, Promponas VJ (1 Jul 2015).
24:
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690:10.1093/bioinformatics/17.suppl_1.s288
7:
831:Kuznetsov IB, Hwang S (1 May 2006).
14:
913:He D, Parkinson J (1 Apr 2008).
608:10.1093/bioinformatics/16.10.915
966:(Web server issue): W435–W440.
872:Li X, Kahveci T (15 Dec 2006).
790:Shin SW, Kim SM (15 Jan 2005).
649:10.1093/bioinformatics/18.5.672
761:10.1080/07391102.2003.10506882
1:
1070:10.1093/bioinformatics/btv115
932:10.1093/bioinformatics/btn073
891:10.1093/bioinformatics/btl495
850:10.1093/bioinformatics/btl049
809:10.1093/bioinformatics/bth497
1115:10.1016/0097-8485(93)85010-a
525:10.1016/0097-8485(93)85006-X
1191:Briefings in Bioinformatics
1146:10.1093/gigascience/giad101
538:Harrison PM (13 Nov 2017).
1384:
726:10.1089/106652703321825955
557:10.1186/s12859-017-1906-3
458:Proc Natl Acad Sci U S A
1021:10.1093/database/baq031
513:Computers and Chemistry
1305:Nucleic Acids Research
1248:Nucleic Acids Research
683:(Suppl 1): S288–S295.
479:10.1073/pnas.89.6.2002
1260:10.1093/nar/gkaa339
749:J Biomol Struct Dyn
470:1992PNAS...89.2002B
1317:10.1093/nar/gkz730
1311:(19): 9998–10009.
1203:10.1093/bib/bbz007
972:10.1093/nar/gkp254
544:BMC Bioinformatics
1368:Lists of software
1064:(13): 2208–2210.
1009:Database (Oxford)
960:Nucleic Acids Res
884:(24): 2980–2987.
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671:Wise MJ (2001).
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1103:Computers Chem
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796:Bioinformatics
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413:downloadable
392:downloadable
258:downloadable
156:downloadable
105:downloadable
82:downloadable
57:downloadable
37:Description
31:Last update
17:
15:
1134:GigaScience
347:on request
282:on request
236:on request
217:on request
198:on request
179:on request
1363:Proteomics
1357:Categories
1015:: baq031.
550:(1): 476.
439:References
43:Reference
1325:0305-1048
1268:0305-1048
1211:1467-5463
1154:2047-217X
1343:31504783
1286:32421769
1229:30698641
1172:38091509
1163:10716826
1088:25712690
1039:21216786
990:19389726
941:18304932
900:17018537
859:16500936
818:15333459
777:45635217
769:12643768
734:12804090
699:11473020
658:12050063
617:11120681
576:29132292
296:SubSeqer
211:ScanCom
1334:6821194
1277:7319588
1220:7299295
1079:4481844
1030:3017391
981:2703921
567:5684748
498:1549558
466:Bibcode
1341:
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406:AlcoR
173:Oj.py
148:SIMPLE
34:Usage
773:S2CID
489:48584
409:2022
388:1993
366:2015
344:2011
323:2009
319:ANNIE
300:2008
279:2006
254:2006
233:2005
230:CARD
214:2003
195:2003
176:2001
152:2002
129:2000
101:2017
78:1993
53:1992
28:Name
1339:PMID
1321:ISSN
1282:PMID
1264:ISSN
1225:PMID
1207:ISSN
1168:PMID
1150:ISSN
1084:PMID
1035:PMID
1013:2011
986:PMID
937:PMID
896:PMID
855:PMID
814:PMID
765:PMID
730:PMID
695:PMID
654:PMID
613:PMID
572:PMID
494:PMID
420:yes
399:yes
385:XNU
276:GBA
269:yes
250:BIAS
192:DSR
166:yes
125:CAST
117:yes
97:fLPS
89:yes
75:SEG
68:yes
49:SAPS
1329:PMC
1313:doi
1272:PMC
1256:doi
1215:PMC
1199:doi
1158:PMC
1142:doi
1111:doi
1074:PMC
1066:doi
1025:PMC
1017:doi
976:PMC
968:doi
927:doi
886:doi
845:doi
804:doi
757:doi
722:doi
685:doi
644:doi
603:doi
562:PMC
552:doi
521:doi
484:PMC
474:doi
378:no
370:web
354:no
334:no
327:web
311:no
304:web
288:no
262:web
242:no
223:no
204:no
185:no
159:web
140:no
133:web
109:web
61:web
1359::
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