Introduction to Data Mining for the Life Sciences

✍ Scribed by Rob Sullivan (auth.)

• Publisher: Humana Press
• Year: 2012
• Tongue: English
• Leaves: 654
• Edition: 1
• Category: Library

✦ Synopsis

Data mining provides a set of new techniques to integrate, synthesize, and analyze tdata, uncovering the hidden patterns that exist within. Traditionally, techniques such as kernel learning methods, pattern recognition, and data mining, have been the domain of researchers in areas such as artificial intelligence, but leveraging these tools, techniques, and concepts against your data asset to identify problems early, understand interactions that exist and highlight previously unrealized relationships through the combination of these different disciplines can provide significant value for the investigator and her organization.

✦ Table of Contents

Front Matter....Pages i-xvii
Introduction....Pages 1-31
Fundamental Concepts....Pages 33-83
Data Architecture and Data Modeling....Pages 85-123
Representing Data Mining Results....Pages 125-190
The Input Side of the Equation....Pages 191-234
Statistical Methods....Pages 235-302
Bayesian Statistics....Pages 303-361
Machine-Learning Techniques....Pages 363-454
Classification and Prediction....Pages 455-500
Informatics....Pages 501-542
Systems Biology....Pages 543-583
Let’s Call It a Day....Pages 585-591
Back Matter....Pages 593-635

✦ Subjects

Bioinformatics