Module section description: Machine learning (ML) is a subfield of artificial intelligence (AI). Basically ML consists of training data base what is introduced in some kind of learning algorithm (programmed system that automatically learn and improve with experience) what cores out trained learning machine. Consequently trained learning machine is used to study a problem we are interested. ML serves to solve classification, time series prediction, regression and clustering tasks. Some learning machines: Linear models, Kernel methods, neural networks, decision trees. Some practical examples of application of ML in the systems biology - a) gene discovery that may be connected to cancer or other diseases by analyzing patterns of gene expression obtained from DNA; b) protein structure and function prediction; c) screening people for certain diseases; d) diagnosis and prognosis of treatment; e) drug discovery; f) etc.

Guyon I. Introduction to ML / videolectures.net

MLSB07 conference materials - ML in systems biology / videolectures.net

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Sternberg M. J. E., et al. Application of machine learning to structural molecular biology. Philosophical Transactions: Biological Sciences - v.344 (1310), (1994) pp 365–371