Title |
Classifying transcription factor targets and discovering relevant biological features
|
---|---|
Published in |
Biology Direct, May 2008
|
DOI | 10.1186/1745-6150-3-22 |
Pubmed ID | |
Authors |
Dustin T Holloway, Mark Kon, Charles DeLisi |
Abstract |
An important goal in post-genomic research is discovering the network of interactions between transcription factors (TFs) and the genes they regulate. We have previously reported the development of a supervised-learning approach to TF target identification, and used it to predict targets of 104 transcription factors in yeast. We now include a new sequence conservation measure, expand our predictions to include 59 new TFs, introduce a web-server, and implement an improved ranking method to reveal the biological features contributing to regulation. The classifiers combine 8 genomic datasets covering a broad range of measurements including sequence conservation, sequence overrepresentation, gene expression, and DNA structural properties. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Italy | 2 | 6% |
Norway | 1 | 3% |
Kenya | 1 | 3% |
Finland | 1 | 3% |
United Kingdom | 1 | 3% |
Denmark | 1 | 3% |
Unknown | 29 | 81% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 10 | 28% |
Researcher | 8 | 22% |
Professor > Associate Professor | 5 | 14% |
Student > Bachelor | 4 | 11% |
Student > Postgraduate | 2 | 6% |
Other | 5 | 14% |
Unknown | 2 | 6% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 17 | 47% |
Engineering | 5 | 14% |
Biochemistry, Genetics and Molecular Biology | 4 | 11% |
Computer Science | 3 | 8% |
Mathematics | 1 | 3% |
Other | 2 | 6% |
Unknown | 4 | 11% |