| Record ID | marc_columbia/Columbia-extract-20221130-011.mrc:285969919:3127 |
| Source | marc_columbia |
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LEADER: 03127cam a22003734a 4500
001 5463838
005 20221110042239.0
008 050202t20062006maua b 001 0 eng
010 $a 2005042803
015 $aGBA560481$2bnb
016 7 $a013255561$2Uk
020 $a0262025914 (alk. paper)
035 $a(OCoLC)ocm57625716
035 $a(NNC)5463838
035 $a5463838
040 $aDLC$cDLC$dUKM$dBAKER$dC#P$dOrLoB-B
042 $apcc
050 00 $aQH324.2$b.B33 2006
082 00 $a572.8/0285$222
100 1 $aBaclawski, Kenneth.$0http://id.loc.gov/authorities/names/nb2003074848
245 10 $aOntologies for bioinformatics /$cKenneth Baclawski, Tianhua Niu.
260 $aCambridge, Mass. :$bMIT Press,$c[2006], ©2006.
300 $axiv, 424 pages :$billustrations ;$c24 cm.
336 $atext$btxt$2rdacontent
337 $aunmediated$bn$2rdamedia
490 1 $aComputational molecular biology
504 $aIncludes bibliographical references (p. [393]-412) and index.
505 00 $gI.$tIntroduction to ontologies -- $g1.$tHierarchies and relationships -- $g2.$tXML semantics -- $g3.$tRules and inference -- $g4.$tThe semantic Web and bioinformatics applications -- $g5.$tSurvey of ontologies in bioinformatics -- $gII.$tBuilding and using ontologies -- $g6.$tInformation retrieval -- $g7.$tSequence similarity searching tools -- $g8.$tQuery languages -- $g9.$tThe transformation process -- $g10.$tTransforming with traditional programming languages -- $g11.$tThe XML transformation language -- $g12.$tBuilding bioinformatics ontologies -- $gIII.$tReasoning with uncertainty -- $g13.$tInductive vs. deductive reasoning -- $g14.$tBayesian networks -- $g15.$tCombining information -- $g16.$tThe Bayesian Web -- $g17.$tAnswers to selected exercises.
520 1 $a"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."--BOOK JACKET.
650 0 $aBioinformatics$xMethodology.
650 12 $aComputational Biology$xmethods.$0https://id.nlm.nih.gov/mesh/D019295Q000379
700 1 $aNiu, Tianhua.$0http://id.loc.gov/authorities/names/n2005008357
830 0 $aComputational molecular biology.$0http://id.loc.gov/authorities/names/no2001017947
852 00 $boff,hsl$hQH324.2$i.B33 2006