Home > Publications database > pydca v1.0: a comprehensive software for direct coupling analysis of RNA and protein sequences > print

001     875075
005     20210130004840.0
024 7 _ |a 10.1093/bioinformatics/btz892
|2 doi
024 7 _ |a 0266-7061
|2 ISSN
024 7 _ |a 1367-4803
|2 ISSN
024 7 _ |a 1367-4811
|2 ISSN
024 7 _ |a 1460-2059
|2 ISSN
024 7 _ |a 2128/24703
|2 Handle
024 7 _ |a altmetric:71334309
|2 altmetric
024 7 _ |a pmid:31778142
|2 pmid
024 7 _ |a WOS:000536489400043
|2 WOS
037 _ _ |a FZJ-2020-01786
082 _ _ |a 570
100 1 _ |a Zerihun, Mehari B
|0 P:(DE-Juel1)179110
|b 0
|u fzj
245 _ _ |a pydca v1.0: a comprehensive software for direct coupling analysis of RNA and protein sequences
260 _ _ |a Oxford
|c 2020
|b Oxford Univ. Press
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1595508349_4402
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a The ongoing advances in sequencing technologies have provided a massive increase inthe availability of sequence data. This made it possible to study the patterns of correlated substitutionbetween residues in families of homologous proteins or RNAs and to retrieve structural and stabilityinformation. Direct coupling Analysis (DCA) infers coevolutionary couplings between pairs of residuesindicating their spatial proximity, making such information a valuable input for subsequent structureprediction. Here we presentpydca, a standalone Python-based software package for the DCA ofprotein- and RNA-homologous families. It is based on two popular inverse statistical approaches,namely, the mean-field and the pseudo-likelihood maximization and is equipped with a series offunctionalities that range from multiple sequence alignment trimming to contact map visualization.Thanks to its efficient implementation, features and user-friendly command line interface,pydcaisa modular and easy-to-use tool that can be used by researchers with a wide range of backgrounds.
536 _ _ |a 511 - Computational Science and Mathematical Methods (POF3-511)
|0 G:(DE-HGF)POF3-511
|c POF3-511
|f POF III
|x 0
536 _ _ |0 G:(DE-Juel1)PHD-NO-GRANT-20170405
|x 1
|c PHD-NO-GRANT-20170405
|a PhD no Grant - Doktorand ohne besondere Förderung (PHD-NO-GRANT-20170405)
588 _ _ |a Dataset connected to CrossRef
700 1 _ |a Pucci, Fabrizio
|0 P:(DE-Juel1)177018
|b 1
|u fzj
700 1 _ |a Peter, Emanuel K
|0 P:(DE-Juel1)177673
|b 2
|u fzj
700 1 _ |a Schug, Alexander
|0 P:(DE-Juel1)173652
|b 3
|e Corresponding author
773 _ _ |a 10.1093/bioinformatics/btz892
|g Vol. 36, no. 7, p. 2264 - 2265
|0 PERI:(DE-600)1468345-3
|n 7
|p 2264 - 2265
|t Bioinformatics
|v 36
|y 2020
|x 1460-2059
856 4 _ |u https://juser.fz-juelich.de/record/875075/files/805523v1.full.pdf
|y Published on 2019-11-28. Available in OpenAccess from 2020-11-28.
856 4 _ |u https://juser.fz-juelich.de/record/875075/files/btz892.pdf
|y Restricted
856 4 _ |u https://juser.fz-juelich.de/record/875075/files/pydca.pdf
|y Published on 2019-11-28. Available in OpenAccess from 2020-11-28.
856 4 _ |u https://juser.fz-juelich.de/record/875075/files/805523v1.full.pdf?subformat=pdfa
|x pdfa
|y Published on 2019-11-28. Available in OpenAccess from 2020-11-28.
856 4 _ |u https://juser.fz-juelich.de/record/875075/files/btz892.pdf?subformat=pdfa
|x pdfa
|y Restricted
856 4 _ |u https://juser.fz-juelich.de/record/875075/files/pydca.pdf?subformat=pdfa
|x pdfa
|y Published on 2019-11-28. Available in OpenAccess from 2020-11-28.
909 C O |o oai:juser.fz-juelich.de:875075
|p openaire
|p open_access
|p VDB
|p driver
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)179110
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)177018
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 2
|6 P:(DE-Juel1)177673
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 3
|6 P:(DE-Juel1)173652
913 1 _ |a DE-HGF
|b Key Technologies
|1 G:(DE-HGF)POF3-510
|0 G:(DE-HGF)POF3-511
|2 G:(DE-HGF)POF3-500
|v Computational Science and Mathematical Methods
|x 0
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF3
|l Supercomputing & Big Data
914 1 _ |y 2020
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1030
|2 StatID
|b Current Contents - Life Sciences
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
915 _ _ |a Embargoed OpenAccess
|0 StatID:(DE-HGF)0530
|2 StatID
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b BIOINFORMATICS : 2017
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
915 _ _ |a WoS
|0 StatID:(DE-HGF)0110
|2 StatID
|b Science Citation Index
915 _ _ |a WoS
|0 StatID:(DE-HGF)0111
|2 StatID
|b Science Citation Index Expanded
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
915 _ _ |a IF >= 5
|0 StatID:(DE-HGF)9905
|2 StatID
|b BIOINFORMATICS : 2017
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0310
|2 StatID
|b NCBI Molecular Biology Database
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0320
|2 StatID
|b PubMed Central
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)JSC-20090406
|k JSC
|l Jülich Supercomputing Center
|x 0
920 1 _ |0 I:(DE-Juel1)NIC-20090406
|k NIC
|l John von Neumann - Institut für Computing
|x 1
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)JSC-20090406
980 _ _ |a I:(DE-Juel1)NIC-20090406
980 _ _ |a UNRESTRICTED
980 1 _ |a FullTexts

LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21