Introduction to Machine Learning and Bioinformatics

Sushmita Mitra, Sujay Datta, Theodore Perkins, George Michailidis (Autoren)

Buch | Hardcover

384 Seiten

2008
Chapman & Hall/CRC (Verlag)
9781584886822 (ISBN)

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Presents an introduction to the basic ideas and developments in machine learning and bioinformatics. This book describes various problems in bioinformatics and the concepts and algorithms of machine learning. It demonstrates the capabilities of key machine learning techniques, such as hidden Markov models and artificial neural networks.

Lucidly Integrates Current Activities

Focusing on both fundamentals and recent advances, Introduction to Machine Learning and Bioinformatics presents an informative and accessible account of the ways in which these two increasingly intertwined areas relate to each other.

Examines Connections between Machine Learning & Bioinformatics

The book begins with a brief historical overview of the technological developments in biology. It then describes the main problems in bioinformatics and the fundamental concepts and algorithms of machine learning. After forming this foundation, the authors explore how machine learning techniques apply to bioinformatics problems, such as electron density map interpretation, biclustering, DNA sequence analysis, and tumor classification. They also include exercises at the end of some chapters and offer supplementary materials on their website.

Explores How Machine Learning Techniques Can Help Solve Bioinformatics Problems

Shedding light on aspects of both machine learning and bioinformatics, this text shows how the innovative tools and techniques of machine learning help extract knowledge from the deluge of information produced by today’s biological experiments.

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

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.

Erscheint lt. Verlag	5.6.2008
Zusatzinfo	19 Tables, black and white; 1 Halftones, black and white; 62 Illustrations, black and white
Sprache	englisch
Maße	156 x 234 mm
Gewicht	1080 g
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
Themenwelt	Naturwissenschaften ► Biologie
ISBN-13	9781584886822 / 9781584886822
Zustand	Neuware