Evidence map›Paper›PMID 17003135›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2006

Genomic analysis of the hierarchical structure of regulatory networks.

Haiyuan Yu, Mark Gerstein

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 157 papers.

0numbers the graph read from it
0cells of the map it votes in
157citing papers in PubMed
8.1field-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

157 citing papers in PubMed, 358 citations in OpenAlex.

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  5. Transcriptome-wide root causal inference.PLoS computational biology · 2025
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  14. Minimal frustration underlies the usefulness of incomplete regulatory network models in biology.Proceedings of the National Academy of Sciences of the United States of America · 2023
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97 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

2 authors at 1 institution in 1 country.

Haiyuan YuDepartment of Molecular Biophysics and Biochemistry, Program in Computational Biology and Bioinformatics, Yale University, 266 Whitney Avenue, P.O. Box 208114, New Haven, CT 06520, USA. haiyuan.yu@yale.edu
Mark Gerstein
Whitney Museum of American Art · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A fundamental question in biology is how the cell uses transcription factors (TFs) to coordinate the expression of thousands of genes in response to various stimuli. The relationships between TFs and their target genes can be modeled in terms of directed regulatory networks. These relationships, in turn, can be readily compared with commonplace "chain-of-command" structures in social networks, which have characteristic hierarchical layouts. Here, we develop algorithms for identifying generalized hierarchies (allowing for various loop structures) and use these approaches to illuminate extensive pyramid-shaped hierarchical structures existing in the regulatory networks of representative prokaryotes (Escherichia coli) and eukaryotes (Saccharomyces cerevisiae), with most TFs at the bottom levels and only a few master TFs on top. These masters are situated near the center of the protein-protein interaction network, a different type of network from the regulatory one, and they receive most of the input for the whole regulatory hierarchy through protein interactions. Moreover, they have maximal influence over other genes, in terms of affecting expression-level changes. Surprisingly, however, TFs at the bottom of the regulatory hierarchy are more essential to the viability of the cell. Finally, one might think master TFs achieve their wide influence through directly regulating many targets, but TFs with most direct targets are in the middle of the hierarchy. We find, in fact, that these midlevel TFs are "control bottlenecks" in the hierarchy, and this great degree of control for "middle managers" has parallels in efficient social structures in various corporate and governmental settings.

Indexed as

Cluster AnalysisEscherichia coliEscherichia coli ProteinsGene Expression Regulation, BacterialGene Expression Regulation, FungalGenome, BacterialGenome, FungalModels, BiologicalProtein BindingSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsTranscription FactorsEscherichia coli ProteinsSaccharomyces cerevisiae ProteinsTranscription Factors

Identifiers

PMID17003135
PMCPMC1595419
OpenAlexW2013326913

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.