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Introduction to Machine Learning and Bioinformatics (Paperback): Sushmita Mitra, Sujay Datta, Theodore Perkins, George... Introduction to Machine Learning and Bioinformatics (Paperback)
Sushmita Mitra, Sujay Datta, Theodore Perkins, George Michailidis
R2,097 Discovery Miles 20 970 Ships in 12 - 17 working days

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.

Introduction to Machine Learning and Bioinformatics (Hardcover): Sushmita Mitra, Sujay Datta, Theodore Perkins, George... Introduction to Machine Learning and Bioinformatics (Hardcover)
Sushmita Mitra, Sujay Datta, Theodore Perkins, George Michailidis
R4,590 Discovery Miles 45 900 Ships in 12 - 17 working days

"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.

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