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1. |
Record Nr. |
UNINA9910376175103321 |
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Autore |
Bononi Luciano |
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Titolo |
PE-WASUN '08 : proceedings of the fifth ACM International Symposium on Performance Evaluation of Wireless Ad-Hoc, Sensor, and Ubiquitous Networks : Vancouver, British Columbia, Canada, October 27-28, 2008 |
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Pubbl/distr/stampa |
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[Place of publication not identified], : ACM, 2008 |
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Descrizione fisica |
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1 online resource (102 pages) |
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Collana |
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Soggetti |
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Engineering & Applied Sciences |
Computer Science |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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2. |
Record Nr. |
UNINA9910483148503321 |
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Titolo |
Regulatory Genomics : RECOMB 2004 International Workshop, RRG 2004, San Diego, CA, USA, March 26-27, 2004, Revised Selected Papers / / edited by Eleazar Eskin, Chris Workman |
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Pubbl/distr/stampa |
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Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2005 |
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Edizione |
[1st ed. 2005.] |
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Descrizione fisica |
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1 online resource (VIII, 116 p.) |
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Collana |
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Lecture Notes in Bioinformatics, , 2366-6331 ; ; 3318 |
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Altri autori (Persone) |
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EskinEleazar |
WorkmanChris |
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Disciplina |
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Soggetti |
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Biochemistry |
Algorithms |
Computer science - Mathematics |
Discrete mathematics |
Artificial intelligence - Data processing |
Database management |
Bioinformatics |
Discrete Mathematics in Computer Science |
Data Science |
Database Management |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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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 |
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Sommario/riassunto |
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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. |
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