Bioinformatics (Record no. 293797)

MARC details
000 -LEADER
fixed length control field 01929nam a2200157Ia 4500
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 8179926427
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 572.8 BAC-B
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Kenneth Baclawski
245 ## - TITLE STATEMENT
Title Bioinformatics
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Mumbai
Name of publisher, distributor, etc. Jaico Publishing House
Date of publication, distribution, etc. 2007
300 ## - PHYSICAL DESCRIPTION
Extent ix, 424 p.
520 ## - SUMMARY, ETC.
Summary, etc. Recent advances in biotechnology, spurred by the Human Genome Project, have resulted in the accumulation of vast amounts of new data. Ontologies - computer-readable, precise formulations of concepts (and the relationship among them) in a given field - are a critical framework for coping with the exponential growth of valuable biological data generated by high-output technologies. This book introduces the key concepts and applications of ontologies and ontology languages in bioinformatics and will be an essential guide for bioinformaticists, computer scientists, and life science researchers.The three parts of Ontologies for Bioinformatics ask, and answer, three pivotal questions: what ontologies are; how ontologies are used; and what ontologies could be (which focuses on how ontologies could be used for reasoning with uncertainty). The authors first introduce the notion of an ontology, from hierarchically organized ontologies to more general network organizations, and survey the best-known ontologies in biology and medicine. They show how to construct and use ontologies, classifying uses into three categories: querying, viewing, and transforming data to serve diverse purposes. Contrasting deductive, or Boolean, logic with inductive reasoning, they describe the goal of a synthesis that supports both styles of reasoning. They discuss Bayesian networks as a way of expressing uncertainty, describe data fusion, and propose that the World Wide Web can be extended to support reasoning with uncertainty. They call this inductive reasoning web the Bayesian web.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Bioinformatics
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Tianhua Niu
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Book
Holdings
Withdrawn status Lost status Damaged status Not for loan Home library Current library Shelving location Date acquired Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type
        Dept. of Computational Biology and Bioinformatics Dept. of Computational Biology and Bioinformatics Processing Center 01/09/2015   572.8 BAC-B DCB391 08/02/2024 01/09/2015 Book