VISIONET: intuitive visualisation of overlapping transcription factor networks, with applications in cardiogenic gene discovery
Author(s)
Type
Journal Article
Abstract
Background
Existing de novo software platforms have largely overlooked a valuable resource, the expertise of the intended biologist users. Typical data representations such as long gene lists, or highly dense and overlapping transcription factor networks often hinder biologists from relating these results to their expertise.
Results
VISIONET, a streamlined visualisation tool built from experimental needs, enables biologists to transform large and dense overlapping transcription factor networks into sparse human-readable graphs via numerically filtering. The VISIONET interface allows users without a computing background to interactively explore and filter their data, and empowers them to apply their specialist knowledge on far more complex and substantial data sets than is currently possible. Applying VISIONET to the Tbx20-Gata4 transcription factor network led to the discovery and validation of Aldh1a2, an essential developmental gene associated with various important cardiac disorders, as a healthy adult cardiac fibroblast gene co-regulated by cardiogenic transcription factors Gata4 and Tbx20.
Conclusions
We demonstrate with experimental validations the utility of VISIONET for expertise-driven gene discovery that opens new experimental directions that would not otherwise have been identified.
Existing de novo software platforms have largely overlooked a valuable resource, the expertise of the intended biologist users. Typical data representations such as long gene lists, or highly dense and overlapping transcription factor networks often hinder biologists from relating these results to their expertise.
Results
VISIONET, a streamlined visualisation tool built from experimental needs, enables biologists to transform large and dense overlapping transcription factor networks into sparse human-readable graphs via numerically filtering. The VISIONET interface allows users without a computing background to interactively explore and filter their data, and empowers them to apply their specialist knowledge on far more complex and substantial data sets than is currently possible. Applying VISIONET to the Tbx20-Gata4 transcription factor network led to the discovery and validation of Aldh1a2, an essential developmental gene associated with various important cardiac disorders, as a healthy adult cardiac fibroblast gene co-regulated by cardiogenic transcription factors Gata4 and Tbx20.
Conclusions
We demonstrate with experimental validations the utility of VISIONET for expertise-driven gene discovery that opens new experimental directions that would not otherwise have been identified.
Date Issued
2015-05-01
Date Acceptance
2015-04-20
Citation
BMC Bioinformatics, 2015, 16
ISSN
1471-2105
Publisher
BioMed Central
Journal / Book Title
BMC Bioinformatics
Volume
16
Copyright Statement
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
License URL
Subjects
Science & Technology
Life Sciences & Biomedicine
Biochemical Research Methods
Biotechnology & Applied Microbiology
Mathematical & Computational Biology
Biochemistry & Molecular Biology
Visualisation
Human-readable
Gene expression
Transcription factor
Network overlap
HEART DEVELOPMENT
SYSTEMS BIOLOGY
MOUSE
GATA4
CHALLENGES
REPRESSOR
SOFTWARE
DELETION
PLATFORM
DISEASE
Adult
Cells, Cultured
Computer Graphics
Fibroblasts
GATA4 Transcription Factor
Gene Expression Regulation, Developmental
Gene Regulatory Networks
Genetic Association Studies
Heart
Humans
Software
T-Box Domain Proteins
Transcription Factors
Bioinformatics
06 Biological Sciences
08 Information And Computing Sciences
01 Mathematical Sciences
Publication Status
Published
Article Number
141