# TFInfer: a tool for probabilistic inference of transcription factor activities

Matthew D. Rolfe
Jeff Green
Neil D. Lawrence, University of Sheffield
Magnus Rattray, University of Manchester
Guido Sanguinetti, University of Edinburgh

Bioinformatics 26, pp 2635-2636

#### Abstract

Summary: TFInfer is a novel open access, standalone tool for genome-wide inference of transcription factor activities from gene expression data. Based on an earlier MATLAB version, the software has now been extended in a number of ways. It has been significantly optimised in terms of performance, and it was given novel functionality, by allowing the user to model both time series and data from multiple independent conditions. With a full documentation and intuitive graphical user interface, together with an in-built data base of yeast and Escherichia coli transcription factors, the software does not require any mathematical or computational expertise to be used effectively.\ Availability: http://homepages.inf.ed.ac.uk/gsanguin/TFInfer.html Contact: gsanguin@staffmail.ed.ac.uk

  @Article{asif-tfinfer10, title = {TFInfer: a tool for probabilistic inference of transcription factor activities}, journal = {Bioinformatics}, author = {H. M. Shahzad Asif and Matthew D. Rolfe and Jeff Green and Neil D. Lawrence and Magnus Rattray and Guido Sanguinetti}, pages = {2635}, year = {2010}, volume = {26}, month = {00}, edit = {https://github.com/lawrennd//publications/edit/gh-pages/_posts/2010-01-01-asif-tfinfer10.md}, url = {http://inverseprobability.com/publications/asif-tfinfer10.html}, abstract = {**Summary**: TFInfer is a novel open access, standalone tool for genome-wide inference of transcription factor activities from gene expression data. Based on an earlier MATLAB version, the software has now been extended in a number of ways. It has been significantly optimised in terms of performance, and it was given novel functionality, by allowing the user to model both time series and data from multiple independent conditions. With a full documentation and intuitive graphical user interface, together with an in-built data base of yeast and Escherichia coli transcription factors, the software does not require any mathematical or computational expertise to be used effectively.\ **Availability**: **Contact**: [gsanguin@staffmail.ed.ac.uk](gsanguin@staffmail.ed.ac.uk)}, key = {Asif-tfinfer10}, linkpdf = {http://bioinformatics.oxfordjournals.org/content/26/20/2635.full.pdf+html}, OPTgroup = {} }
 %T TFInfer: a tool for probabilistic inference of transcription factor activities %A H. M. Shahzad Asif and Matthew D. Rolfe and Jeff Green and Neil D. Lawrence and Magnus Rattray and Guido Sanguinetti %B %C Bioinformatics %D %F asif-tfinfer10 %J Bioinformatics %P 2635--2636 %R %U http://inverseprobability.com/publications/asif-tfinfer10.html %V 26 %X **Summary**: TFInfer is a novel open access, standalone tool for genome-wide inference of transcription factor activities from gene expression data. Based on an earlier MATLAB version, the software has now been extended in a number of ways. It has been significantly optimised in terms of performance, and it was given novel functionality, by allowing the user to model both time series and data from multiple independent conditions. With a full documentation and intuitive graphical user interface, together with an in-built data base of yeast and Escherichia coli transcription factors, the software does not require any mathematical or computational expertise to be used effectively.\ **Availability**: **Contact**: [gsanguin@staffmail.ed.ac.uk](gsanguin@staffmail.ed.ac.uk) 
 TY - CPAPER TI - TFInfer: a tool for probabilistic inference of transcription factor activities AU - H. M. Shahzad Asif AU - Matthew D. Rolfe AU - Jeff Green AU - Neil D. Lawrence AU - Magnus Rattray AU - Guido Sanguinetti PY - 2010/01/01 DA - 2010/01/01 ID - asif-tfinfer10 SP - 2635 EP - 2636 L1 - http://bioinformatics.oxfordjournals.org/content/26/20/2635.full.pdf+html UR - http://inverseprobability.com/publications/asif-tfinfer10.html AB - **Summary**: TFInfer is a novel open access, standalone tool for genome-wide inference of transcription factor activities from gene expression data. Based on an earlier MATLAB version, the software has now been extended in a number of ways. It has been significantly optimised in terms of performance, and it was given novel functionality, by allowing the user to model both time series and data from multiple independent conditions. With a full documentation and intuitive graphical user interface, together with an in-built data base of yeast and Escherichia coli transcription factors, the software does not require any mathematical or computational expertise to be used effectively.\ **Availability**: **Contact**: [gsanguin@staffmail.ed.ac.uk](gsanguin@staffmail.ed.ac.uk) ER - 
 Asif, H.M.S., Rolfe, M.D., Green, J., Lawrence, N.D., Rattray, M. & Sanguinetti, G.. (2010). TFInfer: a tool for probabilistic inference of transcription factor activities. Bioinformatics 26:2635-2636