Learning Methodologies for Detection and Classification of Mutagens

Abstract

Predicting mutagenicity is a complex and challenging problem in chemoinformatics. Ames test is a biological method to assess mutagenicity of molecules. The dynamic growth in the repositories of molecules establishes a need to develop and apply effective and efficient computational techniques to solving chemoinformatics problems such as identification and classification of mutagens. Machine learning methods provide effective solutions to chemoinformatics problems. This chapter presents an overview of the learning techniques that have been developed and applied to the problem of identification and classification of mutagens.