Logos: a modular bayesian model for de novo motif detection.
about
A survey of DNA motif finding algorithmsMotifPrototyper: a Bayesian profile model for motif familiesPractical strategies for discovering regulatory DNA sequence motifs.Assessment of composite motif discovery methods.A feature-based approach to modeling protein-DNA interactionsMTAP: the motif tool assessment platform.A survey of motif discovery methods in an integrated frameworkMethod of predicting splice sites based on signal interactionsCompo: composite motif discovery using discrete modelsRecent computational approaches to understand gene regulation: mining gene regulation in silico.Comparative analysis of regulatory motif discovery tools for transcription factor binding sites.Refining motifs by improving information content scores using neighborhood profile search.PIDA:A new algorithm for pattern identification.Joint learning of gene functions--a Bayesian network model approach.A Mixture Model Based Markov Random Field for Discovering Patterns in SequencesBayesian Unsupervised Learning of DNA Regulatory Binding Regions
P2860
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P2860
Logos: a modular bayesian model for de novo motif detection.
description
2004 nî lūn-bûn
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2004年の論文
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2004年学术文章
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2004年学术文章
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2004年学术文章
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2004年学术文章
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2004年学术文章
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2004年學術文章
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name
Logos: a modular bayesian model for de novo motif detection.
@en
Logos: a modular bayesian model for de novo motif detection.
@nl
type
label
Logos: a modular bayesian model for de novo motif detection.
@en
Logos: a modular bayesian model for de novo motif detection.
@nl
prefLabel
Logos: a modular bayesian model for de novo motif detection.
@en
Logos: a modular bayesian model for de novo motif detection.
@nl
P2860
P1476
Logos: a modular bayesian model for de novo motif detection.
@en
P2093
P2860
P304
P356
10.1142/S0219720004000508
P577
2004-03-01T00:00:00Z