A practical comparison of methods for detecting transcription factor binding sites in ChIP-seq experiments

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1471-2164

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: A practical comparison of methods for detecting transcription factor binding sites in ChIP-seq experiments ; volume:10 ; number:1 ; day:18 ; month:12 ; year:2009 ; pages:1-15 ; date:12.2009
BMC genomics ; 10, Heft 1 (18.12.2009), 1-15, 12.2009

Creator: Laajala, Teemu D.

Contributor: Raghav, Sunil
Tuomela, Soile
Lahesmaa, Riitta
Aittokallio, Tero
Elo, Laura L.
SpringerLink (Online service)

DOI: 10.1186/1471-2164-10-618

URN: urn:nbn:de:1111-201607281630

Rights: Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 14.08.2025, 10:59 AM CEST

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Laajala, Teemu D.
Raghav, Sunil
Tuomela, Soile
Lahesmaa, Riitta
Aittokallio, Tero
Elo, Laura L.
SpringerLink (Online service)

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Virtual ChIP-seq: predicting transcription factor binding by learning from the transcriptome

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Shape-based peak identification for ChIP-Seq

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Detecting broad domains and narrow peaks in ChIP-seq data with hiddenDomains

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The ChIP-Seq tools and web server: a resource for analyzing ChIP-seq and other types of genomic data

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Pinpointing transcription factor binding sites from ChIP-seq data with SeqSite

zweidimensionales bewegtes Bild

Virtual ChIP-seq: Predicting transcription factor binding by learning from the transcriptome

Virtual ChIP-seq: predicting transcription factor binding by learning from the transcriptome

Model-based Analysis of ChIP-Seq (MACS)

Shape-based peak identification for ChIP-Seq

Normalization of ChIP-seq data with control

Detecting broad domains and narrow peaks in ChIP-seq data with hiddenDomains

Non-targeted transcription factors motifs are a systemic component of ChIP-seq datasets

The ChIP-Seq tools and web server: a resource for analyzing ChIP-seq and other types of genomic data

RELACS nuclei barcoding enables high-throughput ChIP-seq

ChIPseqR: analysis of ChIP-seq experiments

BayesPeak: Bayesian analysis of ChIP-seq data

Pinpointing transcription factor binding sites from ChIP-seq data with SeqSite

zweidimensionales bewegtes Bild

Virtual ChIP-seq: Predicting transcription factor binding by learning from the transcriptome

Virtual ChIP-seq: predicting transcription factor binding by learning from the transcriptome

Model-based Analysis of ChIP-Seq (MACS)

Shape-based peak identification for ChIP-Seq

Normalization of ChIP-seq data with control

Detecting broad domains and narrow peaks in ChIP-seq data with hiddenDomains

Non-targeted transcription factors motifs are a systemic component of ChIP-seq datasets

The ChIP-Seq tools and web server: a resource for analyzing ChIP-seq and other types of genomic data

RELACS nuclei barcoding enables high-throughput ChIP-seq

ChIPseqR: analysis of ChIP-seq experiments

BayesPeak: Bayesian analysis of ChIP-seq data

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A practical comparison of methods for detecting transcription factor binding sites in ChIP-seq experiments

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Other Objects (12)

Pinpointing transcription factor binding sites from ChIP-seq data with SeqSite

Virtual ChIP-seq: Predicting transcription factor binding by learning from the transcriptome

Virtual ChIP-seq: predicting transcription factor binding by learning from the transcriptome

Model-based Analysis of ChIP-Seq (MACS)

Shape-based peak identification for ChIP-Seq

Normalization of ChIP-seq data with control

Detecting broad domains and narrow peaks in ChIP-seq data with hiddenDomains

Non-targeted transcription factors motifs are a systemic component of ChIP-seq datasets

The ChIP-Seq tools and web server: a resource for analyzing ChIP-seq and other types of genomic data

RELACS nuclei barcoding enables high-throughput ChIP-seq

ChIPseqR: analysis of ChIP-seq experiments

BayesPeak: Bayesian analysis of ChIP-seq data

Pinpointing transcription factor binding sites from ChIP-seq data with SeqSite

Virtual ChIP-seq: Predicting transcription factor binding by learning from the transcriptome

Virtual ChIP-seq: predicting transcription factor binding by learning from the transcriptome

Model-based Analysis of ChIP-Seq (MACS)

Shape-based peak identification for ChIP-Seq

Normalization of ChIP-seq data with control

Detecting broad domains and narrow peaks in ChIP-seq data with hiddenDomains

Non-targeted transcription factors motifs are a systemic component of ChIP-seq datasets

The ChIP-Seq tools and web server: a resource for analyzing ChIP-seq and other types of genomic data

RELACS nuclei barcoding enables high-throughput ChIP-seq

ChIPseqR: analysis of ChIP-seq experiments

BayesPeak: Bayesian analysis of ChIP-seq data

Pinpointing transcription factor binding sites from ChIP-seq data with SeqSite

Virtual ChIP-seq: Predicting transcription factor binding by learning from the transcriptome

Virtual ChIP-seq: predicting transcription factor binding by learning from the transcriptome

Model-based Analysis of ChIP-Seq (MACS)

Shape-based peak identification for ChIP-Seq

Normalization of ChIP-seq data with control

Detecting broad domains and narrow peaks in ChIP-seq data with hiddenDomains

Non-targeted transcription factors motifs are a systemic component of ChIP-seq datasets

The ChIP-Seq tools and web server: a resource for analyzing ChIP-seq and other types of genomic data

RELACS nuclei barcoding enables high-throughput ChIP-seq

ChIPseqR: analysis of ChIP-seq experiments

BayesPeak: Bayesian analysis of ChIP-seq data

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