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@ARTICLE{Zerihun:875075,
      author       = {Zerihun, Mehari B and Pucci, Fabrizio and Peter, Emanuel K
                      and Schug, Alexander},
      title        = {pydca v1.0: a comprehensive software for direct coupling
                      analysis of {RNA} and protein sequences},
      journal      = {Bioinformatics},
      volume       = {36},
      number       = {7},
      issn         = {1460-2059},
      address      = {Oxford},
      publisher    = {Oxford Univ. Press},
      reportid     = {FZJ-2020-01786},
      pages        = {2264 - 2265},
      year         = {2020},
      abstract     = {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.},
      cin          = {JSC / NIC},
      ddc          = {570},
      cid          = {I:(DE-Juel1)JSC-20090406 / I:(DE-Juel1)NIC-20090406},
      pnm          = {511 - Computational Science and Mathematical Methods
                      (POF3-511) / PhD no Grant - Doktorand ohne besondere
                      Förderung (PHD-NO-GRANT-20170405)},
      pid          = {G:(DE-HGF)POF3-511 / G:(DE-Juel1)PHD-NO-GRANT-20170405},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:31778142},
      UT           = {WOS:000536489400043},
      doi          = {10.1093/bioinformatics/btz892},
      url          = {https://juser.fz-juelich.de/record/875075},
}