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Automatic generation of bioinformatics tools for predicting protein–ligand binding sites
Author(s) -
Yusuke Komiyama,
Masaki Banno,
Kokoro Ueki,
Gul Saad,
Kentaro Shimizu
Publication year - 2015
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btv593
Subject(s) - computer science , computational biology , bioinformatics , data mining , biology
Predictive tools that model protein-ligand binding on demand are needed to promote ligand research in an innovative drug-design environment. However, it takes considerable time and effort to develop predictive tools that can be applied to individual ligands. An automated production pipeline that can rapidly and efficiently develop user-friendly protein-ligand binding predictive tools would be useful.

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