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Introduction to Data Mining for the Life Sciences (Record no. 17737)

000 -LEADER
fixed length control field 03001nam a22003855i 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20140310150239.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 120106s2012 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781597452908
978-1-59745-290-8
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QH324.2-324.25
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 570.285
Edition number 23
264 #1 -
-- Totowa, NJ :
-- Humana Press,
-- 2012.
912 ## -
-- ZDB-2-SBL
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Sullivan, Rob.
Relator term author.
245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE
Title Introduction to Data Mining for the Life Sciences
Medium [electronic resource] /
Statement of responsibility, etc by Rob Sullivan.
300 ## - PHYSICAL DESCRIPTION
Extent XVIII, 638 p.
Other physical details online resource.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Introduction -- Fundamental Concepts -- Data Architecture and Data Modeling -- Representing Data Mining Results -- The Input Side of the Equation -- Statistical Methods -- Bayesian Statistics -- Machine Learning Techniques -- Classification and Prediction -- Informatics -- Systems Biology -- Let’s Call it a Day -- Appendix A -- Appendix B -- Appendix C. Appendix D -- Index.
520 ## - SUMMARY, ETC.
Summary, etc 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.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Life sciences.
Topical term or geographic name as entry element Bioinformatics.
Topical term or geographic name as entry element Life Sciences.
Topical term or geographic name as entry element Bioinformatics.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9781588299420
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-1-59745-290-8
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type E-Book
Copies
Price effective from Permanent location Date last seen Not for loan Date acquired Source of classification or shelving scheme Koha item type Damaged status Lost status Withdrawn status Current location Full call number
2014-04-05AUM Main Library2014-04-05 2014-04-05 E-Book   AUM Main Library570.285