Virtual ChIP-seq: predicting transcription factor binding by learning from the transcriptome
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1474-760X
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Anmerkungen
-
online resource.
- Erschienen in
-
Virtual ChIP-seq: predicting transcription factor binding by learning from the transcriptome ; volume:23 ; number:1 ; day:10 ; month:6 ; year:2022 ; pages:1-23 ; date:12.2022
Genome biology ; 23, Heft 1 (10.6.2022), 1-23, 12.2022
- Urheber
-
Karimzadeh, Mehran
Hoffman, Michael M.
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
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10.1186/s13059-022-02690-2
- URN
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urn:nbn:de:101:1-2022082020232995858206
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:30 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
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Beteiligte
- Karimzadeh, Mehran
- Hoffman, Michael M.
- SpringerLink (Online service)
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Model-based Analysis of ChIP-Seq (MACS)
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RELACS nuclei barcoding enables high-throughput ChIP-seq
ChIPseqR: analysis of ChIP-seq experiments
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HyperChIP: identification of hypervariable signals across ChIP-seq or ATAC-seq samples