04766nam 22008415 450 991048314850332120251226195056.010.1007/b105490(CKB)1000000000212699(SSID)ssj0000319791(PQKBManifestationID)11227258(PQKBTitleCode)TC0000319791(PQKBWorkID)10338581(PQKB)11290976(DE-He213)978-3-540-32280-1(MiAaPQ)EBC3067989(PPN)123091608(BIP)11530560(EXLCZ)99100000000021269920100701d2005 u| 0engurnn|008mamaatxtccrRegulatory Genomics RECOMB 2004 International Workshop, RRG 2004, San Diego, CA, USA, March 26-27, 2004, Revised Selected Papers /edited by Eleazar Eskin, Chris Workman1st ed. 2005.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2005.1 online resource (VIII, 116 p.) Lecture Notes in Bioinformatics,2366-6331 ;3318Bibliographic Level Mode of Issuance: MonographPrinted edition: 9783540244561 Includes bibliographical references and index.Predicting Genetic Regulatory Response Using Classification: Yeast Stress Response -- Detecting Functional Modules of Transcription Factor Binding Sites in the Human Genome -- Fishing for Proteins in the Pacific Northwest -- PhyloGibbs: A Gibbs Sampler Incorporating Phylogenetic Information -- Application of Kernel Method to Reveal Subtypes of TF Binding Motifs -- Learning Regulatory Network Models that Represent Regulator States and Roles -- Using Expression Data to Discover RNA and DNA Regulatory Sequence Motifs -- Parameter Landscape Analysis for Common Motif Discovery Programs -- Inferring Cis-region Hierarchies from Patterns in Time-Course Gene Expression Data -- Modeling and Analysis of Heterogeneous Regulation in Biological Networks.Research in the ?eld of gene regulation is evolving rapidly in an ever-changing s- enti'c environment. Microarray techniques and comparative genomics have enabled more comprehensive studies of regulatory genomics and are proving to be powerful tools of discovery. The application of chromatin immunoprecipitation and microarrays (chIP-on-chip) to directly study the genomic binding locations of transcription factors has enabled more comprehensive modeling of regulatory networks. In addition, c- plete genome sequences and the comparison of numerous related species has dem- strated that conservation in non-coding DNA sequences often provides evidence for cis-regulatory binding sites. That said, much is still to be learned about the regulatory networks of these sequenced genomes. Systematic methods to decipher the regulatory mechanism are also crucial for c- roboratingthese regulatorynetworks.Thecoreof thesemethodsarethe motifdiscovery algorithms that can help predict cis-regulatory elements. These DNA-motif discovery programsarebecomingmoresophisticatedandare beginningto leverageevidencefrom comparative genomics (phylogenetic footprinting) and chIP-on-chip studies. How to use these new sources of evidence is an active area of research.Lecture Notes in Bioinformatics,2366-6331 ;3318BiochemistryAlgorithmsComputer scienceMathematicsDiscrete mathematicsArtificial intelligenceData processingDatabase managementBioinformaticsBiochemistryAlgorithmsDiscrete Mathematics in Computer ScienceData ScienceDatabase ManagementBioinformaticsBiochemistry.Algorithms.Computer scienceMathematics.Discrete mathematics.Artificial intelligenceData processing.Database management.Bioinformatics.Biochemistry.Algorithms.Discrete Mathematics in Computer Science.Data Science.Database Management.Bioinformatics.572Eskin Eleazar1652094Workman Chris1763076International Conference on Research in Computational Molecular Biology(8th :2004 :San Diego, Calif.)MiAaPQMiAaPQMiAaPQBOOK9910483148503321Regulatory genomics4203333UNINA