Open AccessA Novel Automated Lazy Learning QSAR (ALL-QSAR) Approach: Method Development, Applications, and Virtual Screening of Chemical Databases Using Validated ALL-QSAR Models
Author(s) -
Shuxing Zhang,
Alexander Gelbukh,
Scott Oloff,
Harold Kohn,
Alexander Tropsha
Publication year - 2006
Publication title -
carolina digital repository (university of north carolina at chapel hill)
Language(s) - English
DOI - 10.17615/acf2-ds75
Subject(s) - quantitative structure–activity relationship , virtual screening , computer science , artificial intelligence , machine learning , database , data mining , chemistry , drug discovery , biochemistry