Evidence map›Paper›PMID 15287978›Full record

ArticleGenome biology2004

Identifying combinatorial regulation of transcription factors and binding motifs.

Mamoru Kato, Naoya Hata, Nilanjana Banerjee, Bruce Futcher, Michael Q Zhang

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers.

0numbers the graph read from it
0cells of the map it votes in
85citing papers in PubMed
7.4field-weighted citation impact, top 2% of its field
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

85 citing papers in PubMed, 174 citations in OpenAlex.

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  12. FisherMP: fully parallel algorithm for detecting combinatorial motifs from large ChIP-seq datasets.DNA research : an international journal for rapid publication of reports on genes and genomes · 2019
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25 more citing papers are in PubMed but not listed here.

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

5 authors at 2 institutions in 2 countries.

Mamoru KatoHuman Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan.
Naoya Hata
Nilanjana Banerjee
Bruce Futcher
Michael Q Zhang
Cold Spring Harbor Laboratory · USStony Brook University · US

Funding

COMPUTATIONAL ANALYSIS OF GENOME EXPRESSION DATAR01GM060513 · NIGMS · COLD SPRING HARBOR LABORATORY · PI ZHANG, MICHAEL Q · 2000 to 2002
$898k
NIGMS NIH HHS 1R01GM60513NIGMS NIH HHS GM64813101NIGMS NIH HHS R01 GM060513
6 · The paper itself

Abstract

backgroundCombinatorial interaction of transcription factors (TFs) is important for gene regulation. Although various genomic datasets are relevant to this issue, each dataset provides relatively weak evidence on its own. Developing methods that can integrate different sequence, expression and localization data have become important.

resultsHere we use a novel method that integrates chromatin immunoprecipitation (ChIP) data with microarray expression data and with combinatorial TF-motif analysis. We systematically identify combinations of transcription factors and of motifs. The various combinations of TFs involved multiple binding mechanisms. We reconstruct a new combinatorial regulatory map of the yeast cell cycle in which cell-cycle regulation can be drawn as a chain of extended TF modules. We find that the pairwise combination of a TF for an early cell-cycle phase and a TF for a later phase is often used to control gene expression at intermediate times. Thus the number of distinct times of gene expression is greater than the number of transcription factors. We also see that some TF modules control branch points (cell-cycle entry and exit), and in the presence of appropriate signals they can allow progress along alternative pathways.

conclusionsCombining different data sources can increase statistical power as demonstrated by detecting TF interactions and composite TF-binding motifs. The original picture of a chain of simple cell-cycle regulators can be extended to a chain of composite regulatory modules: different modules may share a common TF component in the same pathway or a TF component cross-talking to other pathways.

Indexed as

Gene Expression Regulation, FungalBase SequenceBinding SitesCell CycleChromatin ImmunoprecipitationComputational BiologyGenes, FungalOligonucleotide Array Sequence AnalysisPromoter Regions, GeneticResponse ElementsSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsTranscription FactorsSaccharomyces cerevisiae ProteinsTranscription Factors

Identifiers

PMID15287978
PMCPMC507881
OpenAlexW2098222328

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.