Research in Computational Molecular Biology [[electronic resource] ] : 12th Annual International Conference, RECOMB 2008, Singapore, March 30 - April 2, 2008, Proceedings / / edited by Martin Vingron, Limsoon Wong

• Pubblicazione: Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2008
• Edizione: 1st ed. 2008.
• Descrizione fisica: 1 online resource (XVI, 480 p.)
• Disciplina: 572.80285
• Soggetto topico: Algorithms; Data structures (Computer science); Computer science—Mathematics; Database management; Artificial intelligence; Bioinformatics; Algorithm Analysis and Problem Complexity; Data Structures; Discrete Mathematics in Computer Science; Database Management; Artificial Intelligence; Computational Biology/Bioinformatics
• Persona (resp. second.): VingronMartin; WongLimsoon
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Computational Biology: Its Challenges Past, Present, and Future -- Bootstrapping the Interactome: Unsupervised Identification of Protein Complexes in Yeast -- CompostBin: A DNA Composition-Based Algorithm for Binning Environmental Shotgun Reads -- Reconstructing the Evolutionary History of Complex Human Gene Clusters -- Ab Initio Whole Genome Shotgun Assembly with Mated Short Reads -- Orchestration of DNA Methylation -- BayCis: A Bayesian Hierarchical HMM for Cis-Regulatory Module Decoding in Metazoan Genomes -- A Combined Expression-Interaction Model for Inferring the Temporal Activity of Transcription Factors -- A Fast, Alignment-Free, Conservation-Based Method for Transcription Factor Binding Site Discovery -- The Statistical Power of Phylogenetic Motif Models -- Transcriptional Regulation and Cancer Genomics -- Automatic Recognition of Cells (ARC) for 3D Images of C. elegans -- Spectrum Fusion: Using Multiple Mass Spectra for De Novo Peptide Sequencing -- A Fragmentation Event Model for Peptide Identification by Mass Spectrometry -- A Bayesian Approach to Protein Inference Problem in Shotgun Proteomics -- De Novo Sequencing of Nonribosomal Peptides -- Systems Metabolic Engineering -- Protein Function Prediction Based on Patterns in Biological Networks -- Automatic Parameter Learning for Multiple Network Alignment -- An Integrative Network Approach to Map the Transcriptome to the Phenome -- Fast and Accurate Alignment of Multiple Protein Networks -- High-Resolution Modeling of Cellular Signaling Networks -- At the Origin of Life: How Did Folded Proteins Evolve? -- Locating Multiple Gene Duplications through Reconciled Trees -- Rapid and Accurate Protein Side Chain Prediction with Local Backbone Information -- Algorithms for Joint Optimization of Stability and Diversity in Planning Combinatorial Libraries of Chimeric Proteins -- DLIGHT – Lateral Gene Transfer Detection Using Pairwise Evolutionary Distances in a Statistical Framework -- Computation of Median Gene Clusters -- BCL-2: From Translocation to Therapy -- Detecting Disease-Specific Dysregulated Pathways Via Analysis of Clinical Expression Profiles -- Constructing Treatment Portfolios Using Affinity Propagation -- Bubbles: Alternative Splicing Events of Arbitrary Dimension in Splicing Graphs -- More Efficient Algorithms for Closest String and Substring Problems -- Disruption of a Transcriptional Regulatory Pathway Contributes to Phenotypes in Carriers of Ataxia Telangiectasia -- Accounting for Non-genetic Factors Improves the Power of eQTL Studies -- Effects of Genetic Divergence in Identifying Ancestral Origin Using HAPAA -- On the Inference of Ancestries in Admixed Populations -- Increasing Power in Association Studies by Using Linkage Disequilibrium Structure and Molecular Function as Prior Information -- Panel Construction for Mapping in Admixed Populations Via Expected Mutual Information -- Constructing Level-2 Phylogenetic Networks from Triplets -- Accurate Computation of Likelihoods in the Coalescent with Recombination Via Parsimony.
• Titolo autorizzato: Research in Computational Molecular Biology
• ISBN: 3-540-78839-5
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 996465499603316
• Lo trovi qui: Univ. di Salerno
• Serie: Lecture Notes in Bioinformatics ; ; 4955