Skip Navigation


Bioinformatics Advance Access originally published online on December 15, 2008
Bioinformatics 2009 25(3):419-420; doi:10.1093/bioinformatics/btn639
This Article
Right arrow Full Text
Right arrow Full Text (Print PDF)
Right arrow Supplementary Data
Right arrow All Versions of this Article:
25/3/419    most recent
btn639v1
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Barenco, M.
Right arrow Articles by Hubank, M.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Barenco, M.
Right arrow Articles by Hubank, M.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

rHVDM: an R package to predict the activity and targets of a transcription factor

M. Barenco 1, E. Papouli 1, S. Shah 2, D. Brewer 3, C.J. Miller 4 and M. Hubank 1,*

1Institute of Child Health, University College London (UCL), 30 Guilford street, London WC1N 1EH, 2Bloomsbury Centre for Bioinformatics, UCL and Birkbeck College, Gower street, London WC1E 6BT, 3The Institute of Cancer Research, 15 Cotswold Rd, Belmont, Sutton, Surrey SM2 5NG and 4Cancer research UK, Paterson Institute for Cancer Research, The University of Manchester, Manchester M20 4BX, UK

*To whom correspondence should be addressed.


  Abstract

Summary: Highly parallel genomic platforms like microarrays often present researchers with long lists of differentially expressed genes but contain little or no information on how these genes are regulated. rHVDM is a novel R package which uses gene expression time course data to predict the activity and targets of a transcription factor. In the first step, rHVDM uses a small number of known targets to derive the activity profile of a given transcription factor. Then, in a subsequent step, this activity profile is used to predict other putative targets of that transcription factor. A dynamic and mechanistic model of gene expression is at the heart of the technique. Measurement error is taken into account during the process, which allows an objective assessment of the robustness of fit and, therefore, the quality of the predictions. The package relies on efficient algorithms and vectorization to accomplish potentially time consuming tasks including optimization and differential equation integration. We demonstrate the efficiency and accuracy of rHVDM by examining the activity of the tumour-suppressing transcription factor, p53.

Availability: The version of the package presented here (1.8.1) is freely available from the Bioconductor Web site (http://bioconductor.org/packages/2.3/bioc/html/rHVDM.html).

Contact: m.barenco{at}ucl.ac.uk

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Martin Bishop

Received on November 11, 2008; revised on December 9, 2008; accepted on December 9, 2008

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.