LEADER 05753nam 2200721Ia 450 001 9910450862603321 005 20200520144314.0 010 $a1-281-86710-1 010 $a9786611867102 010 $a1-86094-729-8 035 $a(CKB)1000000000406131 035 $a(EBL)296217 035 $a(OCoLC)246970846 035 $a(SSID)ssj0000228047 035 $a(PQKBManifestationID)11196270 035 $a(PQKBTitleCode)TC0000228047 035 $a(PQKBWorkID)10148124 035 $a(PQKB)10361282 035 $a(MiAaPQ)EBC3050874 035 $a(WSP)00000027 035 $a(MiAaPQ)EBC296217 035 $a(Au-PeEL)EBL3050874 035 $a(CaPaEBR)ebr10188366 035 $a(CaONFJC)MIL186710 035 $a(OCoLC)922951701 035 $a(Au-PeEL)EBL296217 035 $a(EXLCZ)991000000000406131 100 $a20060419d2006 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aProceedings of the 4th Asia-Pacific Bioinformatics Conference$b[electronic resource] $eTaipei, Taiwan, 13-16 February 2006 /$feditors, Tao Jiang ... [et al.] 210 $aLondon $cImperial College Press ;$aHackensack, NJ $cDistributed by World Scientific$dc2006 215 $a1 online resource (379 p.) 225 1 $aSeries on advances in bioinformatics and computational biology ;$vv. 3 300 $aDescription based upon print version of record. 311 $a1-86094-623-2 320 $aIncludes bibliographical references and index. 327 $aPreface; APBC 2006 Organization; Programme Committee; CONTENTS; Keynote Papers; Contributed Papers; Wen-Hsiung Li. On the Inference of Regulatory Elements, Circuits and Modules; Mark A. Ragan. Automating the Search for Lateral Gene Transfer; Michael S. Waterman. Whole Genome Optical Mapping; D.A. Konovalov. Accuracy of Four Heuristics for the Full Sibship Reconstruction Problem in the Presence of Genotype Errors; 1 Introduction; 2 Method; 2.1 Accuracy; 2.2 Simulations; 3 Algorithms; 3.1 The Modified SIMPSON (MS2) Algorithm; 3.2 The SIMPSON-assisted Descending Ratio (SDR) Algorithm 327 $a4 Results and Discussion Acknowledgments; References; P.C.H. Ma & K.C.C. Chan. Inference of Gene Regulatory Networks from Microarray Data: A Fuzzy Logic Approach; 1 Introduction; 2 The proposed algorithm; 2.1. Linguistic variables and linguistic terms representation; 2.2. Discovering the interesting patterns; 2.3. Prediction based on the discovered patterns; 3 Experimental results; 3.1. Experimental data; 3.2. Method of evaluating the results; 3.3. Results; 3.4. Biological interpretation; 4 Conclusions; References 327 $aC.W. Li, W.C. Chang, & B.S. Chen. System Identification and Robustness Analysis of the Circadian Regulatory Network via Microarray Data in Arabidopsis Thaliana 1 Introduction; 2 Dynamic System Description of Circadian Regulatory Model; 3. Assay of the Model; 3.1. Assay of ARX System Model; 3.1.1. Determination of system order; 3.2. Sensitivity Analysis of Circadian System; 3.2.1. Circadian clock frequency assay; 3.2.2. Trans-perturbation assay; 3.2.2.1. Trans-sensitivity rate Y simulation of gene; 3.2.2.2 Trans-expression threshold M1 simulation of gene; 4. Results; 5. Discussion 327 $aAcknowledgments References; P. Horton, K.-J. Park, T. Obayashi, & K. Nakai. Protein Subcellular Localization Prediction with WOLF PSORT; 1. Introduction; 2. Methods; 2.1. Dataset; 2.1.1. Site Definition; 2.2. WoLF PSORT system; 2.3. Classification; 2.3.1. Candidate Features; 2.3.2. Classification Algorithm; 2.3.3. Extensions for Dual Localization Prediction; 2.3.4. Feature Selection and Weighting; 2.3.5. Reducing Over-reliance on Sequence Similarity; 2.3.6. Evaluation of WoLF PSORT Accuracy; 3. Results; 3.1. Effect of Feature Weighting; 3.2. WoLF PSORT Combined with BLAST 327 $a3.3. WoLF PSORT Server 4. Discussion; 4.1. Interpretable Results; 4.2. Evaluation in the Presence of Similar Sequences; 4.3. Predicting Dual Localization; 5. Conclusion; 6. Acknowledgement; References; P.-H. Chi & C.-R. Shyu. Predicting Ranked SCOP Domains by Mining Associations of Visual Contents in Distance Matrices; 1. Introduction; 2. Preliminaries; 3. Method; 3.1. Space Partition Algorithm Using C4.5 Decision Tree; 3.2. Mining Training Data and Prediction Model; 4. Experiment; 5. Conclusion; References; D. Ruths & L. Nakhleh. RECOMP: A Parsimony-Based Method for Detecting Recombination 327 $a1. Introduction 330 $aHigh-throughput sequencing and functional genomics technologies have given us a draft human genome sequence and have enabled large-scale genotyping and gene expression profiling of human populations. Databases containing large numbers of sequences, polymorphisms, and gene expression profiles of normal and diseased tissues in different clinical states are rapidly being generated for human and model organisms. Bioinformatics is thus rapidly growing in importance in the annotation of genomic sequences, in the understanding of the interplay between genes and proteins, in the analysis of the genetics 410 0$aSeries on advances in bioinformatics and computational biology ;$vv. 3. 606 $aBioinformatics$vCongresses 606 $aBiology$xData processing 608 $aElectronic books. 615 0$aBioinformatics 615 0$aBiology$xData processing. 676 $a572.0285 701 $aJiang$b Tao$f1963-$0854413 712 12$aAsia-Pacific Bioinformatics Conference 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910450862603321 996 $aProceedings of the 4th Asia-Pacific Bioinformatics Conference$92476626 997 $aUNINA