VISIONET: intuitive visualisation of overlapping transcription factor networks, with applications in cardiogenic gene discovery

BMC Bioinformatics

Software

Mauro W Costa¹  Milena B Furtado¹  Hieu T Nim²  Sarah E Boyd²  Nadia A Rosenthal³  Hiroaki Kitano⁴ 

[1] Australian Regenerative Medicine Institute, Monash University, 3800, Clayton, VIC, Australia;Systems Biology Institute (SBI) Australia, Monash University, 3800, Clayton, VIC, Australia;Australian Regenerative Medicine Institute, Monash University, 3800, Clayton, VIC, Australia;Systems Biology Institute (SBI) Australia, Monash University, 3800, Clayton, VIC, Australia;Australian Regenerative Medicine Institute, Monash University, 3800, Clayton, VIC, Australia;National Heart and Lung Institute, Imperial College London, W12 0NN, London, UK;Systems Biology Institute (SBI) Australia, Monash University, 3800, Clayton, VIC, Australia;Australian Regenerative Medicine Institute, Monash University, 3800, Clayton, VIC, Australia;Sony Computer Science Laboratories, Inc., Higashigotanda, Shinagawa, Tokyo, Japan;Okinawa Institute of Science and Technology, Onna, Onna-son, Kunigami, Okinawa, Japan;

关键词: Visualisation;    Human-readable;    Gene expression;    Transcription factor;    Network overlap;   

DOI  :  10.1186/s12859-015-0578-0

 received in 2015-01-09, accepted in 2015-04-20,  发布年份 2015

来源: Springer

【 摘 要 】

BackgroundExisting 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.ResultsVISIONET, 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.ConclusionsWe 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.

【 授权许可】

CC BY   
© Nim et al.; licensee BioMed Central. 2015