| Literature DB >> 27467875 |
Alexandre Varnek1, Igor I Baskin2.
Abstract
Here, chemoinformatics is considered as a theoretical chemistry discipline complementary to quantum chemistry and force-field molecular modeling. These three fields are compared with respect to molecular representation, inference mechanisms, basic concepts and application areas. A chemical space, a fundamental concept of chemoinformatics, is considered with respect to complex relations between chemical objects (graphs or descriptor vectors). Statistical Learning Theory, one of the main mathematical approaches in structure-property modeling, is briefly reviewed. Links between chemoinformatics and its "sister" fields - machine learning, chemometrics and bioinformatics are discussed.Keywords: Chemical space; Chemoinformatics; Computational learning theory; Similarity
Year: 2011 PMID: 27467875 DOI: 10.1002/minf.201000100
Source DB: PubMed Journal: Mol Inform ISSN: 1868-1743 Impact factor: 3.353