Information-Theoretic Evaluation for Computational Biomedical Ontologies (Record no. 93066)

000 -LEADER
fixed length control field 02940nam a22005415i 4500
001 - CONTROL NUMBER
control field 978-3-319-04138-4
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20140220082514.0
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 140109s2014 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783319041384
-- 978-3-319-04138-4
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-319-04138-4
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QH324.2-324.25
072 #7 - SUBJECT CATEGORY CODE
Subject category code PSA
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code UB
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM014000
Source bisacsh
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 570.285
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Clark, Wyatt Travis.
Relator term author.
245 10 - TITLE STATEMENT
Title Information-Theoretic Evaluation for Computational Biomedical Ontologies
Medium [electronic resource] /
Statement of responsibility, etc by Wyatt Travis Clark.
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2014.
300 ## - PHYSICAL DESCRIPTION
Extent VII, 46 p. 12 illus., 6 illus. in color.
Other physical details online resource.
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-- computer
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-- online resource
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-- text file
-- PDF
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490 1# - SERIES STATEMENT
Series statement SpringerBriefs in Computer Science,
International Standard Serial Number 2191-5768
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Introduction -- Methods -- Experiments and Results -- Discussion.
520 ## - SUMMARY, ETC.
Summary, etc The development of effective methods for the prediction of ontological annotations is an important goal in computational biology, yet evaluating their performance is difficult due to problems caused by the structure of biomedical ontologies and incomplete annotations of genes. This work proposes an information-theoretic framework to evaluate the performance of computational protein function prediction. A Bayesian network is used, structured according to the underlying ontology, to model the prior probability of a protein's function. The concepts of misinformation and remaining uncertainty are then defined, that can be seen as analogs of precision and recall. Finally, semantic distance is proposed as a single statistic for ranking classification models. The approach is evaluated by analyzing three protein function predictors of gene ontology terms. The work addresses several weaknesses of current metrics, and provides valuable insights into the performance of protein function prediction tools.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer science.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Human genetics.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Medical records
General subdivision Data processing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer software.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Optical pattern recognition.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Bioinformatics.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer Science.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computational Biology/Bioinformatics.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Algorithm Analysis and Problem Complexity.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Human Genetics.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Pattern Recognition.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Health Informatics.
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 9783319041377
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title SpringerBriefs in Computer Science,
-- 2191-5768
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-319-04138-4
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