ReviewComputational and structural biotechnology journal2020
Seq-ing answers: Current data integration approaches to uncover mechanisms of transcriptional regulation.
Review in Computational and structural biotechnology journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- SEgene identifies links between super enhancers and gene expression across cell types.NPJ systems biology and applications · 2025Article
- Article
- CSSQ: a ChIP-seq signal quantifier pipeline.Frontiers in cell and developmental biology · 2023Article
- Article
- Bibliometric review of ATAC-Seq and its application in gene expression.Briefings in bioinformatics · 2022Review
- Transcriptional regulation by a RecQ helicase.Methods in enzymology · 2022Article
- Virtual Gene Concept and a Corresponding Pragmatic Research Program in Genetical Data Science.Entropy (Basel, Switzerland) · 2021Review
- Analysis of H3K4me3-ChIP-Seq and RNA-Seq data to understand the putative role of miRNAs and their target genes in breast cancer cell lines.Genomics & informatics · 2021Article
- The role of epigenetic modifications for the pathogenesis of Crohn's disease.Clinical epigenetics · 2021Review
- Differential chromatin binding of the lung lineage transcription factor NKX2-1 resolves opposing murine alveolar cell fates in vivo.Nature communications · 2021Article
- Genome-in-a-Box: Building a Chromosome from the Bottom Up.ACS nano · 2021Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.