Abstract
Gene regulatory networks inferred from RNA abundance data have generated significant interest, but despite this, gene network approaches are used infrequently and often require input from bioinformaticians. We have assembled a suite of tools for analysing regulatory networks, and we illustrate their use with microarray datasets generated in human endothelial cells. We infer a range of regulatory networks, and based on this analysis discuss the strengths and limitations of network inference from RNA abundance data. We welcome contact from researchers interested in using our inference and visualization tools to answer biological questions.
| Original language | English |
|---|---|
| Pages (from-to) | 2377-2398 |
| Number of pages | 22 |
| Journal | Nucleic acids research |
| Volume | 40 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - Mar 1 2012 |
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All Science Journal Classification (ASJC) codes
- Genetics
Cite this
Gene network inference and visualization tools for biologists : Application to new human transcriptome datasets. / Hurley, Daniel; Araki, Hiromitsu; Tamada, Yoshinori; Dunmore, Ben; Sanders, Deborah; Humphreys, Sally; Affara, Muna; Imoto, Seiya; Yasuda, Kaori; Tomiyasu, Yuki; Tashiro, Kosuke; Savoie, Christopher; Cho, Vicky; Smith, Stephen; Kuhara, Satoru; Miyano, Satoru; Charnock-Jones, D. Stephen; Crampin, Edmund J.; Print, Cristin G.
In: Nucleic acids research, Vol. 40, No. 6, 01.03.2012, p. 2377-2398.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Gene network inference and visualization tools for biologists
T2 - Application to new human transcriptome datasets
AU - Hurley, Daniel
AU - Araki, Hiromitsu
AU - Tamada, Yoshinori
AU - Dunmore, Ben
AU - Sanders, Deborah
AU - Humphreys, Sally
AU - Affara, Muna
AU - Imoto, Seiya
AU - Yasuda, Kaori
AU - Tomiyasu, Yuki
AU - Tashiro, Kosuke
AU - Savoie, Christopher
AU - Cho, Vicky
AU - Smith, Stephen
AU - Kuhara, Satoru
AU - Miyano, Satoru
AU - Charnock-Jones, D. Stephen
AU - Crampin, Edmund J.
AU - Print, Cristin G.
PY - 2012/3/1
Y1 - 2012/3/1
N2 - Gene regulatory networks inferred from RNA abundance data have generated significant interest, but despite this, gene network approaches are used infrequently and often require input from bioinformaticians. We have assembled a suite of tools for analysing regulatory networks, and we illustrate their use with microarray datasets generated in human endothelial cells. We infer a range of regulatory networks, and based on this analysis discuss the strengths and limitations of network inference from RNA abundance data. We welcome contact from researchers interested in using our inference and visualization tools to answer biological questions.
AB - Gene regulatory networks inferred from RNA abundance data have generated significant interest, but despite this, gene network approaches are used infrequently and often require input from bioinformaticians. We have assembled a suite of tools for analysing regulatory networks, and we illustrate their use with microarray datasets generated in human endothelial cells. We infer a range of regulatory networks, and based on this analysis discuss the strengths and limitations of network inference from RNA abundance data. We welcome contact from researchers interested in using our inference and visualization tools to answer biological questions.
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UR - http://www.scopus.com/inward/citedby.url?scp=84859371992&partnerID=8YFLogxK
U2 - 10.1093/nar/gkr902
DO - 10.1093/nar/gkr902
M3 - Article
VL - 40
SP - 2377
EP - 2398
JO - Nucleic Acids Research
JF - Nucleic Acids Research
SN - 0305-1048
IS - 6
ER -