Introduction to Machine Learning and Bioinformatics

ISBN-13: 9780367387235 / Angielski / Miękka / 2019 / 384 str.

Sushmita Mitra; Sujay Datta; Theodore Perkins

Opis

Examining the connections between these two increasingly intertwined areas, this text presents a unifying, thorough, and accessible introduction to the basic ideas and latest developments in machine learning and bioinformatics. It describes the major problems in bioinformatics and the concepts and algorithms of machine learning. The authors demonstrate the capabilities of key machine learning techniques, such as hidden Markov models and artificial neural networks, and apply state-of-the-art techniques to bioinformatics problems in structural biology, cancer treatment, and proteomics. They also include exercises at the end of some chapters and offer instructional materials on their website.

Spis treści

Introduction. The Biology of a Living Organism. Probabilistic and Model-Based Learning. Classification Techniques. Unsupervised Learning Techniques. Computational Intelligence in Bioinformatics. Connections. Machine Learning in Structural Biology. Soft Computing in Biclustering. Bayesian Methods for Tumor Classification. Modeling and Analysis of iTRAQ Data. Mass Spectrometry Classification. Index.

O autorze

Mitra, Sushmita; Datta, Sujay; Perkins, Theodore; Michailidis, George