Evidence map›Paper›PMID 23285197›Full record

ArticlePloS one2012

An integrative approach to inferring gene regulatory module networks.

Michael Baitaluk, Sergey Kozhenkov, Julia Ponomarenko

Abstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Michael BaitalukSan Diego Supercomputer Center, University of California-San Diego, La Jolla, CA, USA.
Sergey Kozhenkov
Julia Ponomarenko

Funding

BiologicalNetworks: Integrated Environment for Systems BiologyR01GM084881 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BAITALUK, MICHAEL · 2008 to 2011
$1.7M
Transcription Factor-DNA Interactions: Structural Classification and PredictionR01GM085325 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PONOMARENKO, JULIA VLADIMIROVNA · 2008 to 2011
$1.1M
NIGMS NIH HHS R01 GM084881NIGMS NIH HHS R01GM084881NIGMS NIH HHS R01 GM085325NIGMS NIH HHS R01GM085325
6 · The paper itself

Abstract

backgroundGene regulatory networks (GRNs) provide insight into the mechanisms of differential gene expression at a system level. However, the methods for inference, functional analysis and visualization of gene regulatory modules and GRNs require the user to collect heterogeneous data from many sources using numerous bioinformatics tools. This makes the analysis expensive and time-consuming.

resultsIn this work, the BiologicalNetworks application-the data integration and network based research environment-was extended with tools for inference and analysis of gene regulatory modules and networks. The backend database of the application integrates public data on gene expression, pathways, transcription factor binding sites, gene and protein sequences, and functional annotations. Thus, all data essential for the gene regulation analysis can be mined publicly. In addition, the user's data can either be integrated in the database and become public, or kept private within the application. The capabilities to analyze multiple gene expression experiments are also provided.

conclusionThe generated modular networks, regulatory modules and binding sites can be visualized and further analyzed within this same application. The developed tools were applied to the mouse model of asthma and the OCT4 regulatory network in embryonic stem cells. Developed methods and data are available through the Java application from BiologicalNetworks program at http://www.biologicalnetworks.org.

Indexed as

Gene Regulatory NetworksAnimalsAsthmaComputational BiologyDatabases, GeneticGene Expression RegulationInternetMiceOctamer Transcription Factor-3SoftwareOctamer Transcription Factor-3Pou5f1 protein, mouse

Identifiers

PMID23285197
PMCPMC3527610

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.