Main logo
tutorial arrow
Create your own tool library
Bookmark tools and put favorites into folders to find them easily.

Crf-based Tfbs Finding system CTF

Predicts transcription factor binding sties (TFBSs). CTF is based on Conditional Random Fields (CRFs) and can capture sophisticated dependency and integrate information from different sources. The software can be a useful complement to ChIP-seq and other experimental methods for TFBS identification. It was evaluated on 13 TFBS datasets with three types of features,(i) the Position Weight Matrix(PWM), (ii) the distance to Transcription start sites (TSS proximity), and (iii) histone markers.

User report

tutorial arrow
Vote up tools and offer feedback
Give value to tools and make your expertise visible
Give your feedback on this tool
Sign up for free to join and share with the community

0 user reviews

0 user reviews

No review has been posted.

CTF forum

tutorial arrow
Communicate with other users
Participate in the forum to get support for using tools. Ask questions about technical specifications.
Take part in the discussion
Sign up for free to ask question and share your advices

No open topic.

CTF classification

CTF specifications

Software type:
Restrictions to use:
Academic or non-commercial use
Computer skills:
Command line interface
Operating system:

CTF distribution


tutorial arrow
Upload and version your source code
Get a DOI for each update to improve tool traceability. Archive your releases so the community can easily visualize progress on your work.
Facilitate your tool traceability
Sign up for free to upload your code and get a DOI

No versioning.


CTF support


  • Chaochun Wei <>


tutorial arrow
Promote your skills
Define all the tasks you managed and assign your profile the appropriate badges. Become an active member.
Promote your work
Sign up for free to badge your contributorship



School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China; Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China; Shanghai Center for Bioinformation Technology, Shanghai, China; Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA

Funding source(s)

Supported by grants from the National Natural Science Foundation of China (60970050, 31100957), the Shanghai Pujiang Program (09PJ1407900), K.C. Wong Education Foundation, Hong Kong and China Postdoctoral Science Foundation fund (20110490758).

Link to literature

By using OMICtools you acknowledge that you have read and accepted the terms of the end user license agreement.