Seq-ing answers: Current data integration approaches to uncover
mechanisms of transcriptional regulation.
Comp. Struc. Biotech. J. 18, 1330-1341 (2020)
Advancements in the field of next generation sequencing lead to the
generation of ever-more data, with the challenge often being how to
combine and reconcile results from different OMICs studies such as
genome, epigenome and transcriptome. Here we provide an overview of the
standard processing pipelines for ChIP-seq and RNA-seq as well as common
downstream analyses. We describe popular multi-omics data integration
approaches used to identify target genes and co-factors, and we discuss
how machine learning techniques may predict transcriptional regulators
and gene expression.
Impact Factor
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Publication type
Article: Journal article
Document type
Review
Thesis type
Editors
Keywords
ChIP-seq; RNA-seq; NGS; Data integration; Multi-omics; Transcriptional regulation; Differential Expression Analysis; Factor-binding Sites; False Discovery Rate; Gene-expression; Rna-seq; Chromatin States; Sequence; Dna; Quantification; Single
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Language
english
Publication Year
2020
Prepublished in Year
HGF-reported in Year
2020
ISSN (print) / ISBN
2001-0370
e-ISSN
2001-0370
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Volume: 18,
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Pages: 1330-1341
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Research Network of Computational and Structural Biotechnology (RNCSB)
Publishing Place
Radarweg 29, 1043 Nx Amsterdam, Netherlands
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Reviewing status
Peer reviewed
POF-Topic(s)
90000 - German Center for Diabetes Research
30205 - Bioengineering and Digital Health
30505 - New Technologies for Biomedical Discoveries
Research field(s)
Helmholtz Diabetes Center
Enabling and Novel Technologies
PSP Element(s)
G-501900-227
G-553500-001
G-503800-001
G-503890-001
G-503800-004
Grants
Helmholtz Association ICEMED
ERC StG SILENCE
Copyright
Erfassungsdatum
2020-06-24