Publication Details (including relevant citation information):
Varnek, A.; Baskin, I. Mol. Inf., 2011, Vol. 30, Iss. 1, pp. 20-32
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.
Address (URL): http://dx.doi.org/10.1002/minf.201000100