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@ARTICLE{Sitani:890265,
      author       = {Sitani, Divya and Giorgetti, Alejandro and
                      Alfonso‐Prieto, Mercedes and Carloni, Paolo},
      title        = {{R}obust {P}rincipal {C}omponent {A}nalysis‐based
                      {P}rediction of {P}rotein‐{P}rotein {I}nteraction {H}ot
                      spots ( {RBHS} )},
      journal      = {Proteins},
      volume       = {89},
      number       = {6},
      issn         = {1097-0134},
      address      = {New York, NY},
      publisher    = {Wiley-Liss},
      reportid     = {FZJ-2021-00849},
      pages        = {639-647},
      year         = {2021},
      abstract     = {Proteins often exert their function by binding to other
                      cellular partners. The hot spots are key residues for
                      protein-protein binding. Their identification may shed light
                      on the impact of disease associated mutations on protein
                      complexes and help design protein-protein interaction
                      inhibitors for therapy. Unfortunately, current machine
                      learning methods to predict hot spots, suffer from
                      limitations caused by gross errors in the data matrices.
                      Here, we present a novel data pre-processing pipeline that
                      overcomes this problem by recovering a low rank matrix with
                      reduced noise using Robust Principal Component Analysis.
                      Application to existing databases shows the predictive power
                      of the method.},
      cin          = {IAS-5 / INM-9},
      ddc          = {570},
      cid          = {I:(DE-Juel1)IAS-5-20120330 / I:(DE-Juel1)INM-9-20140121},
      pnm          = {525 - Decoding Brain Organization and Dysfunction
                      (POF4-525) / 5241 - Molecular Information Processing in
                      Cellular Systems (POF4-524)},
      pid          = {G:(DE-HGF)POF4-525 / G:(DE-HGF)POF4-5241},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {33458895},
      UT           = {WOS:000613869900001},
      doi          = {10.1002/prot.26047},
      url          = {https://juser.fz-juelich.de/record/890265},
}