Application of machine learning to protein structure prediction and drug design

Author

Sternberg, M.J.E. ; Hirst, Jonathan D. ; Lewis, Richard A. ; King, Ross D. ; Srinivasan, Ashwin ; Muggleton, Stephen

Author_Institution

Biomolecular Modelling Lab., Imperial Cancer Res. Fund., London, UK

fYear

1994

fDate

2/28/1994 12:00:00 AM

Firstpage

42370

Lastpage

42372

Abstract

Machine learning, based on inductive-based logic programming (ILP), has been applied to three problems in bioinformatics. The first topic is the prediction of the local secondary structure of a protein from its sequence. The second is the derivation of rules governing protein β-sheet topology. Finally ILP is used to model quantitatively the structure-activity relationship of a series of drugs

Keywords

biology computing; learning (artificial intelligence); logic programming; macromolecular configurations; molecular biophysics; proteins; bioinformatics; drug design; inductive-based logic programming; local secondary structure; machine learning; protein beta -sheet topology; protein conformation; protein structure prediction; structure-activity relationship;

fLanguage

English

Publisher

iet

Conference_Titel

Molecular Bioinformatics, IEE Colloquium on

Type

conf

Filename

297410

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3571619