Evidence map›Paper›PMID 31942977›Full record

ArticleDatabase : the journal of biological databases and curation2020

ChIPSummitDB: a ChIP-seq-based database of human transcription factor binding sites and the topological arrangements of the proteins bound to them.

Erik Czipa, Mátyás Schiller, Tibor Nagy, Levente Kontra, László Steiner, Júlia Koller, Orsolya Pálné-Szén, Endre Barta

Abstract readDataset
In one paragraph

Article in Database : the journal of biological databases and curation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  7. Long Noncoding RNAs in the Pathogenesis of Insulin Resistance.International journal of molecular sciences · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Erik CzipaDepartment of Biochemistry and Molecular Biology, Faculty of Medicine, University of Debrecen, Egyetem tér 1, Debrecen H-4032, Hungary.
Mátyás SchillerAgricultural Genomics and Bioinformatics Group, Agricultural Biotechnology Institute, National Agricultural Research and Innovation Center, Szent-Györgyi Albert út 4, Gödöllő H-2100, Hungary.
Tibor NagyDepartment of Biochemistry and Molecular Biology, Faculty of Medicine, University of Debrecen, Egyetem tér 1, Debrecen H-4032, Hungary.
Levente KontraDepartment of Biochemistry and Molecular Biology, Faculty of Medicine, University of Debrecen, Egyetem tér 1, Debrecen H-4032, Hungary.
László SteinerUD-GenoMed Medical Genomic Technologies Research & Development Services Ltd., Nagyerdei krt. 98, Debrecen H-4032, Hungary.
Júlia KollerDepartment of Biochemistry and Molecular Biology, Faculty of Medicine, University of Debrecen, Egyetem tér 1, Debrecen H-4032, Hungary.
Orsolya Pálné-SzénDepartment of Biochemistry and Molecular Biology, Faculty of Medicine, University of Debrecen, Egyetem tér 1, Debrecen H-4032, Hungary.
Endre BartaDepartment of Biochemistry and Molecular Biology, Faculty of Medicine, University of Debrecen, Egyetem tér 1, Debrecen H-4032, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

ChIP-seq reveals genomic regions where proteins, e.g. transcription factors (TFs) interact with DNA. A substantial fraction of these regions, however, do not contain the cognate binding site for the TF of interest. This phenomenon might be explained by protein-protein interactions and co-precipitation of interacting gene regulatory elements. We uniformly processed 3727 human ChIP-seq data sets and determined the cistrome of 292 TFs, as well as the distances between the TF binding motif centers and the ChIP-seq peak summits. ChIPSummitDB enables the analysis of ChIP-seq data using multiple approaches. The 292 cistromes and corresponding ChIP-seq peak sets can be browsed in GenomeView. Overlapping SNPs can be inspected in dbSNPView. Most importantly, the MotifView and PairShiftView pages show the average distance between motif centers and overlapping ChIP-seq peak summits and distance distributions thereof, respectively. In addition to providing a comprehensive human TF binding site collection, the ChIPSummitDB database and web interface allows for the examination of the topological arrangement of TF complexes genome-wide. ChIPSummitDB is freely accessible at http://summit.med.unideb.hu/summitdb/. The database will be regularly updated and extended with the newly available human and mouse ChIP-seq data sets.

Indexed as

Chromatin Immunoprecipitation SequencingSequence Analysis, DNATranscription FactorsBinding SitesGenomicsHigh-Throughput Nucleotide SequencingHumansProtein BindingTranscription Factors

Identifiers

PMID31942977
PMCPMC6964213

What OpenQuestion holds

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Registered trials

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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.