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PiPred - a deep-learning method for prediction of π-helices in protein sequences.
Ludwiczak, Jan; Winski, Aleksander; da Silva Neto, Antonio Marinho; Szczepaniak, Krzysztof; Alva, Vikram; Dunin-Horkawicz, Stanislaw.
Affiliation
  • Ludwiczak J; Laboratory of Structural Bioinformatics, Centre of New Technologies, University of Warsaw, Banacha 2c, 02-097, Warsaw, Poland.
  • Winski A; Laboratory of Bioinformatics, Nencki Institute of Experimental Biology, Pasteura 3, 02-093, Warsaw, Poland.
  • da Silva Neto AM; Laboratory of Structural Bioinformatics, Centre of New Technologies, University of Warsaw, Banacha 2c, 02-097, Warsaw, Poland.
  • Szczepaniak K; Laboratory of Structural Bioinformatics, Centre of New Technologies, University of Warsaw, Banacha 2c, 02-097, Warsaw, Poland.
  • Alva V; Laboratory of Structural Bioinformatics, Centre of New Technologies, University of Warsaw, Banacha 2c, 02-097, Warsaw, Poland.
  • Dunin-Horkawicz S; Department of Protein Evolution, Max-Planck-Institute for Developmental Biology, Max-Planck-Ring 5, 72076, Tübingen, Germany.
Sci Rep ; 9(1): 6888, 2019 05 03.
Article in En | MEDLINE | ID: mdl-31053765
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Proteins / Computational Biology / Deep Learning Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Sci Rep Year: 2019 Document type: Article Affiliation country: Poland
Fulltext
Add to My VHL
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Proteins / Computational Biology / Deep Learning Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Sci Rep Year: 2019 Document type: Article Affiliation country: Poland