Introduction to Data Mining for the Life Sciences

  • Rob Sullivan

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Rob Sullivan
    Pages 1-31
  3. Rob Sullivan
    Pages 33-83
  4. Rob Sullivan
    Pages 85-123
  5. Rob Sullivan
    Pages 125-190
  6. Rob Sullivan
    Pages 191-234
  7. Rob Sullivan
    Pages 235-302
  8. Rob Sullivan
    Pages 303-361
  9. Rob Sullivan
    Pages 363-454
  10. Rob Sullivan
    Pages 455-500
  11. Rob Sullivan
    Pages 501-542
  12. Rob Sullivan
    Pages 543-583
  13. Rob Sullivan
    Pages 585-591
  14. Back Matter
    Pages 593-635

About this book

Introduction

One of the major challenges for the scientific community, a challenge that has been seen in many business disciplines, is the exponential increase in data being generated by new experimental techniques and research. A single microarray experiment, for example, can generate thousands of data points that need to be analyzed, and this problem is predicted to increase. As new techniques in areas such as genomics and proteomics continue to be adopted into the mainstream as the costs fall, the need for effective mechanisms for synthesizing these disparate forms of data together for analysis is of paramount importance. But the sheer volume of data means that traditional techniques need to be augmented by approaches that elicit knowledge from the data, using automated procedures.

Data mining provides a set of such techniques, new techniques to integrate, synthesize, and analyze the data, 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.

Keywords

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Authors and affiliations

  • Rob Sullivan
    • 1
  1. 1.CincinnatiUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-59745-290-8
  • Copyright Information Springer Science+Business Media, LLC 2012
  • Publisher Name Humana Press
  • eBook Packages Biomedical and Life Sciences
  • Print ISBN 978-1-58829-942-0
  • Online ISBN 978-1-59745-290-8
  • About this book