Evidence map›Paper›PMID 23268448›Full record

ArticleNucleic acids research2013

TEAK: topology enrichment analysis framework for detecting activated biological subpathways.

Thair Judeh, Cole Johnson, Anuj Kumar, Dongxiao Zhu

Abstract read
In one paragraph

Article in Nucleic acids research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

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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

16 citing papers in PubMed.

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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

4 authors.

Thair JudehDepartment of Computer Science, Wayne State University, 5057 Woodward Avenue, Detroit, MI 48202, USA.
Cole Johnson
Anuj Kumar
Dongxiao Zhu

Funding

A new informatics paradigm for reconstructing signaling pathways in human diseaseR21LM010137 · NLM · WAYNE STATE UNIVERSITY · PI ZHU, DONGXIAO · 2009 to 2010
$500k
NLM NIH HHS R21LM010137PHS HHS 1R01-A1098450-01A1
6 · The paper itself

Abstract

To mine gene expression data sets effectively, analysis frameworks need to incorporate methods that identify intergenic relationships within enriched biologically relevant subpathways. For this purpose, we developed the Topology Enrichment Analysis frameworK (TEAK). TEAK employs a novel in-house algorithm and a tailor-made Clique Percolation Method to extract linear and nonlinear KEGG subpathways, respectively. TEAK scores subpathways using the Bayesian Information Criterion for context specific data and the Kullback-Leibler divergence for case-control data. In this article, we utilized TEAK with experimental studies to analyze microarray data sets profiling stress responses in the model eukaryote Saccharomyces cerevisiae. Using a public microarray data set, we identified via TEAK linear sphingolipid metabolic subpathways activated during the yeast response to nitrogen stress, and phenotypic analyses of the corresponding deletion strains indicated previously unreported fitness defects for the dpl1Δ and lag1Δ mutants under conditions of nitrogen limitation. In addition, we studied the yeast filamentous response to nitrogen stress by profiling changes in transcript levels upon deletion of two key filamentous growth transcription factors, FLO8 and MSS11. Via TEAK we identified a nonlinear glycerophospholipid metabolism subpathway involving the SLC1 gene, which we found via mutational analysis to be required for yeast filamentous growth.

Indexed as

AlgorithmsTranscriptomeDyneinsGene Expression Regulation, FungalGlycerophospholipidsMetabolic Networks and PathwaysNuclear ProteinsSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsSoftwareSphingolipidsStress, PhysiologicalTrans-ActivatorsTranscription FactorsTranscription, GeneticDyneinsFLO8 protein, S cerevisaieGlycerophospholipidsMSS11 protein, S cerevisiaeNuclear ProteinsSaccharomyces cerevisiae ProteinsSLC1 protein, S cerevisiaeSphingolipidsTrans-ActivatorsTranscription Factors

Identifiers

PMID23268448
PMCPMC3561980

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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.