TFInfer: a tool for probabilistic inference of transcription factor activities

H. M. Shahzad Asif; Matthew D. Rolfe; Jeff Green; Neil D. Lawrence; Magnus Rattray; Guido Sanguinetti

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TFInfer: a tool for probabilistic inference of transcription factor activities

H. M. Shahzad Asif, Matthew D. Rolfe, Jeff Green, Neil D. Lawrence, Magnus Rattray, Guido Sanguinetti

Bioinformatics, 26:2635-2636, 2010.

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

Links

Cite this Paper

BibTeX


@Article{Asif-tfinfer10,
  title = 	 {{TFInfer}: a tool for probabilistic inference of transcription factor activities},
  author = 	 {Asif, H. M. Shahzad and Rolfe, Matthew D. and Green, Jeff and Lawrence, Neil D. and Rattray, Magnus and Sanguinetti, Guido},
  journal =      {Bioinformatics},
  pages = 	 {2635--2636},
  year = 	 {2010},
  volume = 	 {26},
  pdf = 	 {http://bioinformatics.oxfordjournals.org/content/26/20/2635.full.pdf+html},
  url = 	 {/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)}
}

Endnote

%0 Journal Article
%T TFInfer: a tool for probabilistic inference of transcription factor activities
%A H. M. Shahzad Asif
%A Matthew D. Rolfe
%A Jeff Green
%A Neil D. Lawrence
%A Magnus Rattray
%A Guido Sanguinetti
%J Bioinformatics
%D 2010	
%F Asif-tfinfer10
%P 2635--2636
%U /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)

RIS


TY  - JOUR
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
DA  - 2010/10/15	
ID  - Asif-tfinfer10
VL  - 26
SP  - 2635
EP  - 2636
L1  - http://bioinformatics.oxfordjournals.org/content/26/20/2635.full.pdf+html
UR  - /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  -

APA


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 Available from /publications/asif-tfinfer10.html.