Evidence map›Paper›PMID 25121490›Full record

ArticlePLoS computational biology2014

Phenotypic robustness and the assortativity signature of human transcription factor networks.

Dov A Pechenick, Joshua L Payne, Jason H Moore

Abstract read
In one paragraph

Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

  1. Article
  2. Systems biology in hepatology: approaches and applications.Nature reviews. Gastroenterology & hepatology · 2018
    Review
  3. Article
  4. Article
  5. Article
  6. Review
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

3 authors.

Dov A PechenickComputational Genetics Laboratory, Dartmouth College, Hanover, New Hampshire, United States of America.
Joshua L PayneInstitute of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.
Jason H MooreComputational Genetics Laboratory, Dartmouth College, Hanover, New Hampshire, United States of America.

Funding

Translational Engineering in Cancer (TEC)P30CA023108 · NCI · DARTMOUTH COLLEGE · PI Steven D Leach · 1985 to 2026
$91.3M
Ultrastructural analysis of axonal Kv2-mediated endoplasmic reticulum/plasma membrane (ER/PM) junctionsP20GM103506 · NIGMS · DARTMOUTH COLLEGE · PI STEVEN FIERING · 2012 to 2026
$60.1M
Quantitative Biology Research InstituteP20GM103534 · NIGMS · DARTMOUTH COLLEGE · PI AMOS, CHRISTOPHER I. · 2012 to 2016
$8.6M
Molecular and Cellular Biology at DartmouthT32GM008704 · NIGMS · DARTMOUTH COLLEGE · PI COMPTON, DUANE A. · 1998 to 2018
$6.8M
Bioinformatics Strategies for Genome-Wide Association StudiesR01LM010098 · NLM · UNIVERSITY OF PENNSYLVANIA · PI MOORE, JASON H., WILLIAMS, SCOTT MATTHEW · 2009 to 2023
$5.1M
Bioinformatics Strategies: Biodefense Vaccine ResearchR01AI059694 · NIAID · DARTMOUTH COLLEGE · PI MOORE, JASON H. · 2004 to 2012
$4.5M
Machine Learning Prediction of Cancer SusceptibilityR01LM009012 · NLM · UNIVERSITY OF PENNSYLVANIA · PI MOORE, JASON H. · 2006 to 2014
$3.3M
NCI NIH HHS P30 CA023108NIAID NIH HHS AI59694NIAID NIH HHS R01 AI059694NIGMS NIH HHS GM103506NIGMS NIH HHS GM103534NIGMS NIH HHS P20 GM103506NIGMS NIH HHS P20 GM103534NIGMS NIH HHS T32 GM008704NIGMS NIH HHS T32GM008704NLM NIH HHS LM009012NLM NIH HHS LM010098NLM NIH HHS R01 LM009012NLM NIH HHS R01 LM010098
6 · The paper itself

Abstract

Many developmental, physiological, and behavioral processes depend on the precise expression of genes in space and time. Such spatiotemporal gene expression phenotypes arise from the binding of sequence-specific transcription factors (TFs) to DNA, and from the regulation of nearby genes that such binding causes. These nearby genes may themselves encode TFs, giving rise to a transcription factor network (TFN), wherein nodes represent TFs and directed edges denote regulatory interactions between TFs. Computational studies have linked several topological properties of TFNs - such as their degree distribution - with the robustness of a TFN's gene expression phenotype to genetic and environmental perturbation. Another important topological property is assortativity, which measures the tendency of nodes with similar numbers of edges to connect. In directed networks, assortativity comprises four distinct components that collectively form an assortativity signature. We know very little about how a TFN's assortativity signature affects the robustness of its gene expression phenotype to perturbation. While recent theoretical results suggest that increasing one specific component of a TFN's assortativity signature leads to increased phenotypic robustness, the biological context of this finding is currently limited because the assortativity signatures of real-world TFNs have not been characterized. It is therefore unclear whether these earlier theoretical findings are biologically relevant. Moreover, it is not known how the other three components of the assortativity signature contribute to the phenotypic robustness of TFNs. Here, we use publicly available DNaseI-seq data to measure the assortativity signatures of genome-wide TFNs in 41 distinct human cell and tissue types. We find that all TFNs share a common assortativity signature and that this signature confers phenotypic robustness to model TFNs. Lastly, we determine the extent to which each of the four components of the assortativity signature contributes to this robustness.

Indexed as

Models, GeneticPhenotypeComputational BiologyGene Expression RegulationGene Regulatory NetworksHumansOrgan SpecificityTranscription FactorsTranscription Factors

Identifiers

PMID25121490
PMCPMC4133045

What OpenQuestion holds

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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.