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@ARTICLE{Pucci:878102,
      author       = {Pucci, Fabrizio and Zerihun, Mehari B. and Peter, Emanuel
                      K. and Schug, Alexander},
      title        = {{E}valuating {DCA}-based method performances for {RNA}
                      contact prediction by a well-curated data set},
      journal      = {RNA},
      volume       = {26},
      number       = {7},
      issn         = {1469-9001},
      address      = {Stanford, Calif.},
      publisher    = {HighWire Press},
      reportid     = {FZJ-2020-02633},
      pages        = {794 - 802},
      year         = {2020},
      abstract     = {RNA molecules play many pivotal roles in a cell that are
                      still not fully understood. Any detailed understanding of
                      RNA function requires knowledge of its three-dimensional
                      structure, yet experimental RNA structure resolution remains
                      demanding. Recent advances in sequencing provide
                      unprecedented amounts of sequence data that can be
                      statistically analyzed by methods such as direct coupling
                      analysis (DCA) to determine spatial proximity or contacts of
                      specific nucleic acid pairs, which improve the quality of
                      structure prediction. To quantify this structure prediction
                      improvement, we here present a well curated data set of
                      about 70 RNA structures of high resolution and compare
                      different nucleotide–nucleotide contact prediction methods
                      available in the literature. We observe only minor
                      differences between the performances of the different
                      methods. Moreover, we discuss how robust these predictions
                      are for different contact definitions and how strongly they
                      depend on procedures used to curate and align the families
                      of homologous RNA sequences.},
      cin          = {JSC},
      ddc          = {610},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {511 - Computational Science and Mathematical Methods
                      (POF3-511) / Forschergruppe Schug $(hkf6_20170901)$ / PhD no
                      Grant - Doktorand ohne besondere Förderung
                      (PHD-NO-GRANT-20170405)},
      pid          = {G:(DE-HGF)POF3-511 / $G:(DE-Juel1)hkf6_20170901$ /
                      G:(DE-Juel1)PHD-NO-GRANT-20170405},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:32276988},
      UT           = {WOS:000541897400003},
      doi          = {10.1261/rna.073809.119},
      url          = {https://juser.fz-juelich.de/record/878102},
}