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



Classifies the protein fold by combing the results from two algorithms, HH-fold and support vector machines (SVM)-fold. TA-fold is an ensemble approach proposed to combine the results of these algorithms. HH-fold is a template-based fold assignment algorithm using the Hidden Markov Model (HMM)-HMM alignment program HHsearch. SVM-fold is a support vector machine-based ab-initio classification algorithm. When there are homologous templates to the query protein, HH-fold prediction is reported. Otherwise, the SVM-fold prediction is returned.

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.

TA-fold 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.

TA-fold classification

TA-fold specifications

Web user interface
Input data:
A protein sequence
Output data:
Predicted fold type
Restrictions to use:
Input format:
Computer skills:

TA-fold support


  • Jianyi Yang <>


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



Department of Physics, Northeast Forestry University, Harbin, China; Center for Applied Mathematics, Tianjin University, Tianjin, China; School of Mathematical Sciences, Nankai University, Tianjin, China

Funding source(s)

The project is supported in part by National Natural Science Foundation of China (11501306, 11501407), China National 863 High-Tech Program (2015AA020101) and the Thousand Youth Talents Plan of China.

Link to literature

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