Computational Identification of MoRFs in Protein Sequences

Terms & Conditions
This software is distributed on an as is basis, without any kind of warranties. This software is for academic not for profit research only. Not for commercial purposes. Incorporating any part of this software in other applications should preserve the Author copyright message. Appropriate citation when using MoRFchibi SYSTEM in publication of scientific results. These UBC Terms of Use set out the terms and conditions that will govern your relationship with UBC, through your use of MoRF_CHibi, including without limitation, your access to the MoRF_CHibi Website, underlying MoRF_CHibi software (the “UBC Software”) through a web browser, web service or other electronic means, uploading data to the MoRF_CHibi Website, downloading data from the MoRF_CHibi Website, searching, using analytical tools or visualizations and other software related services that may be provided by UBC through the MoRF_CHibi Website (the “UBC Services”). You are hereby notified that the UBC Software has been developed and is licensed under the Apache License, Version 2.0 (the “License”); and you may not use the UBC Software except in compliance with the License. You may obtain a copy of the License at UBC disclaims all representation and/or warranties, and bears no responsibility and/or liability for either third party software or the UBC Services. For greater certainty, the “UBC Services” does not include the actual license of the underlying UBC Software to you, which would if requested by you and agreed to by UBC, would be set up through a private installation and governed by a separate license agreement between UBC and you.
For any inquiries, please contact us via Nawar Malhis ( or Joerg Gsponer (
  • Malhis N, Jacobson M, and Gsponer J. MoRFchibi SYSTEM: Software Tools for the Identification of MoRFs in Protein sequences. Nucleic Acids Research (2016), DOI: 10.1093/nar/gkw409.
  • Malhis N, Wong TCE, Nassar R, Gsponer J. Computational Identification of MoRFs in Protein Sequences Using Hierarchical Application of Bayes Rule. PLOS ONE (2015), DOI: 10.1371/journal.pone.0141603.
  • Malhis N, and Gsponer J. Computational Identification of MoRFs in Protein SequencesBioinformatics (2015) 31 (11): 1738-1744.
  • Credits

    Computational MoRF Prediction Software Tool

    Nawar Malhis & Joerg Gsponer

    Fully-Synchronized Job Queueing System & Web Application

    Matthew Jacobson
    JacobsonMT+MoRF [at] gmail [dot] com