MULcDeep

A protein localization prediction tool at sub-cellular and sub-organellar levels

Multiple sequences must be seperated by ids which are new lines started with '>'. If there is no symbol '>', the whole text will be treated as one sequence. (maximum 200 sequences).


 
 

 
 
 
 

Optional

Optional. We will notify you through email when the job is done. (We'll never share your email with anyone else.)

Upload file

Multiple sequences must be seperated by ids which are new lines started with '>'. If there is no symbol '>', the whole text will be treated as one sequence. (maximum 200 sequences).


 
 

 
 
 
 

Optional

Optional. We will notify you through email when the job is done. (We'll never share your email with anyone else.)

What's new
Citation

Jiang Y, Wang D, Yao Y, Eubel H, Künzler P, Møller IM, Xu D. MULocDeep: A deep-learning framework for protein subcellular and suborganellar localization prediction with residue-level interpretation. Comput Struct Biotechnol J. 2021 Aug 18;19:4825-4839. doi: 10.1016/j.csbj.2021.08.027. PMID: 34522290; PMCID: PMC8426535.

Contact us

MULocDeep webservice/stand-alone package are free of charge for academic users; other users are requested to contact the corresponding author of this work at

Dong Xu

Email: xudong@missouri.edu

If you ever have any question or problem using our tool, please contact

Yuexu Jiang

Email: yjm85@mail.missouri.edu

© 2022 Digital Biology Lab (Version 1.7)