LEADER 05394nam 2200697Ia 450 001 9910454291203321 005 20200520144314.0 010 $a1-281-93473-9 010 $a9786611934736 010 $a981-279-484-0 035 $a(CKB)1000000000537795 035 $a(EBL)1679392 035 $a(OCoLC)879023575 035 $a(SSID)ssj0000243610 035 $a(PQKBManifestationID)11188245 035 $a(PQKBTitleCode)TC0000243610 035 $a(PQKBWorkID)10160303 035 $a(PQKB)11205039 035 $a(MiAaPQ)EBC1679392 035 $a(WSP)00005489 035 $a(Au-PeEL)EBL1679392 035 $a(CaPaEBR)ebr10255845 035 $a(CaONFJC)MIL193473 035 $a(EXLCZ)991000000000537795 100 $a20041008d2004 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aSelected topics in post-genome knowledge discovery$b[electronic resource] /$feditor[s], Limsoon Wong, Louxin Zhang 210 $aSingapore $cSingapore University Press ;$aSingapore ;$aRiver Edge, NJ $cWorld Scientific Pub. Co.$dc2004 215 $a1 online resource (176 p.) 225 1 $aLecture notes series ;$vvol. 3 300 $aDescription based upon print version of record. 311 $a981-238-780-3 320 $aIncludes bibliographical references. 327 $aContents ; Foreword ; Preface ; Dynamic Programming Strategies for Analyzing Biomolecular Sequences ; 1. Introduction ; 2. Elementary Dynamic-Programming Algorithms ; 2.1. Fibonacci numbers ; 2.2. The maximum-sum substring problem ; 2.3. Longest increasing subsequence 327 $a2.4. Longest common subsequence 3. Sequence Alignment ; 3.1. Global alignment ; 3.2. Local alignment ; 3.3. Affine gap penalties ; 3.4. Space-saving strategies ; 3.5. Multiple sequence alignment ; The Representation Comparison and Prediction of Protein Pathways ; 1. Introduction 327 $a2. Online Pathway Resources 3. Pathway Representation ; 3.1. Pathway Space ; 3.2. SLIPR Format ; 4. Pathway Comparison ; 4.1. Comparing Individual Components ; 4.2. Aligning Two Pathways Using Dynamic Programming ; 4.3. Pathway Database Comparison 327 $a4.4. One Implementation: PM_search Documentation 5. Orthologous Pathway Prediction ; 6. Discussion ; 6.1. Theoretical Issues on Evolutionary Study of Pathways ; 6.2. Establishing a Relational Pathway Database and its Web Interfaces ; 6.3. Pathway Prediction and Beyond 327 $aGene Network Inference and Biopathway Modeling 1. Introduction ; 2. Gene Network Inference from Microarray Data ; 2.1. Boolean Network Model ; 2.2. Bayesian Network Model ; 3. Modeling and Simulation ; 3.1. Architecture for Biopathway Modeling ; 3.2. How to Model Biopathways 327 $a3.3. Genomic Object Net and Biopathway Databases Towards Simulation 330 $a The Institute for Mathematical Sciences at the National University of Singapore organized a program on "Post-Genome Knowledge Discovery" from January to June 2002. 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