Bayesian Unsupervised Learning of DNA Regulatory Binding Regions

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Bayesian Unsupervised Learning of DNA Regulatory Binding Regions

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wetenschappelijk artikel

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наукова стаття, опублікована у 2009

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Bayesian Unsupervised Learning of DNA Regulatory Binding Regions

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Bayesian Unsupervised Learning of DNA Regulatory Binding Regions

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Bayesian Unsupervised Learning of DNA Regulatory Binding Regions

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Bayesian Unsupervised Learning of DNA Regulatory Binding Regions

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Bayesian Unsupervised Learning of DNA Regulatory Binding Regions

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Bayesian Unsupervised Learning of DNA Regulatory Binding Regions

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P1476

Bayesian Unsupervised Learning of DNA Regulatory Binding Regions

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P2093

Jukka Corander

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Magnus Ekdahl

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Timo Koski

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P2860

Identification of transcription factor binding sites with variable-order Bayesian networks

Assessing computational tools for the discovery of transcription factor binding sites

Detection of functional DNA motifs via statistical over-representation

Reversible jump Markov chain Monte Carlo computation and Bayesian model determination

Efficient exact motif discovery.

Discovery of novel transcription factor binding sites by statistical overrepresentation.

Inching toward reality: an improved likelihood model of sequence evolution.

Studying statistical properties of regulatory DNA sequences, and their use in predicting regulatory regions in the eukaryotic genomes.

Gibbs Recursive Sampler: finding transcription factor binding sites.

Statistical analysis of nucleotide sequences.

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1-11

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scholarly article

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10.1155/2009/219743

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P478

2009

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2009-01-01T00:00:00Z

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