Tree-based position weight matrix approach to model transcription factor binding site profiles (Q34017882)

30 July 2017

title

Tree-based position weight matrix approach to model transcription factor binding site profiles (English)

1 reference

30 July 2017

Yingtao Bi

1

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30 July 2017

Hyunsoo Kim

series ordinal

2

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30 July 2017

Ravi Gupta

series ordinal

3

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30 July 2017

Ramana V Davuluri

series ordinal

4

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30 July 2017

language of work or name

English

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publication date

2 September 2011

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30 July 2017

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30 July 2017

volume

6

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30 July 2017

issue

9

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30 July 2017

page(s)

e24210

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Creative Commons Attribution 4.0 International

30 July 2017

copyright license

start time

2 September 2011

1 reference

April 2022 Public Data File from Crossref

copyright status

copyrighted

0 references

cites work

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Inclusion of neighboring base interdependencies substantially improves genome-wide prokaryotic transcription factor binding site prediction

5 July 2018

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CTCF binding site classes exhibit distinct evolutionary, genomic, epigenomic and transcriptomic features.

5 July 2018

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Functional diversity for REST (NRSF) is defined by in vivo binding affinity hierarchies at the DNA sequence level

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5 July 2018

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5 July 2018

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5 July 2018

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5 July 2018

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5 July 2018

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5 July 2018

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5 July 2018

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5 July 2018

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5 July 2018

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21 January 2018

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21 January 2018

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21 January 2018

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21 January 2018

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Modeling within-motif dependence for transcription factor binding site predictions

21 January 2018

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Enhanced position weight matrices using mixture models

21 January 2018

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https://api.crossref.org/works/10.1371%2FJOURNAL.PONE.0024210

Context-specific independence mixture modeling for positional weight matrices

21 January 2018

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https://api.crossref.org/works/10.1371%2FJOURNAL.PONE.0024210

21 January 2018

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https://api.crossref.org/works/10.1371%2FJOURNAL.PONE.0024210

10.1371/JOURNAL.PONE.0024210

21 January 2018

Identifiers

DOI

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30 July 2017

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30 July 2017

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