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


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-12

AUTHORS

Hieu T Nim, Milena B Furtado, Mauro W Costa, Nadia A Rosenthal, Hiroaki Kitano, Sarah E Boyd

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. More... »

PAGES

141

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12859-015-0578-0

DOI

http://dx.doi.org/10.1186/s12859-015-0578-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1022453385

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/25929466


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s12859-015-0578-0'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s12859-015-0578-0'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s12859-015-0578-0'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s12859-015-0578-0'


 

This table displays all metadata directly associated to this object as RDF triples.

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