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Genetics / DNA / Genomics / Promoter / Sequence alignment / Gene prediction / Noncoding DNA / Cis-regulatory module / VISTA / Biology / Bioinformatics / Gene expression


Downloaded from www.genome.org on December 5, 2006 ESPERR: Learning strong and weak signals in genomic sequence alignments to identify functional elements James Taylor, Svitlana Tyekucheva, David C. King, Ross C. Hardis
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Document Date: 2006-12-05 10:16:00

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ESPERR / Patel / San Diego / Trinklein / /

Company

Chromatin / Multispecies Sequence Analysis / Cambridge University Press / ENCODE Transcriptional Regulation / RP / Gap / Chromosomes / Genes and Transcripts / Cold Spring Harbor Laboratory Press / /

Country

Jordan / United Kingdom / /

Currency

IDR / /

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Event

Business Partnership / /

Facility

The Pennsylvania State University / University Park / /

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IndustryTerm

heuristic search / search procedure / iterative search / transcription start site / computational tools / search algorithm / search iteration / computational learning algorithms / clustering algorithm / related gene-prediction algorithms / heuristic search procedure / /

OperatingSystem

Microsoft Vista / /

Organization

Cambridge University / National Institute of Health / The Pennsylvania State University / Francesca Chiaromonte1 Center for Comparative Genomics and Bioinformatics / /

Person

Francesca Chiaromonte Genome Res / David C. King / Ross C. Hardison / James Taylor / Nat / Taylor et al. Learning / L. Elnitski / Thomas / Svitlana Tyekucheva / Webb Miller / /

Position

D.J. / King / Singer / representative / reporter / candidate / and the candidate / /

ProgrammingLanguage

C / Python / /

ProvinceOrState

North Dakota / Pennsylvania / Y.T. / California / New Hampshire / /

PublishedMedium

Genome Research / /

Technology

Genomics / Bioinformatics / computational learning algorithms / search algorithm / Expectation Maximization algorithm / human genome / genetic code / http / related gene-prediction algorithms / /

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http /

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