Antiprotozoal peptide prediction using machine learning with effective feature selection techniques
The models are incorporated in a user-friendly web server (www.soodlab.com/appred) to predict the antiprotozoal activity of given peptides.
Authors
- Vikas Sood (ORCID: https://orcid.org/0000-0001-6128-4279)
- Yash Goyal (ORCID: https://orcid.org/0000-0002-2496-7422)
- Neha Periwal
- Baljeet Kaur (ORCID: https://orcid.org/0000-0003-2821-2219)
- Anand Singh Rathore (ORCID: https://orcid.org/0009-0004-8907-7174)
- Pooja Arora (ORCID: https://orcid.org/0000-0002-3321-9469)
- Ananya Thakur
- Lakshay Agrawal
- H. S. Anand
Institutions
- University of Delhi (IN)
- University of Waterloo (CA)
- Jamia Hamdard (IN)
Publication Details
- Journal
- Heliyon
- Published
- 2024-08-01
- DOI
- https://doi.org/10.1016/j.heliyon.2024.e36163
- Citations
- 18
- Primary Topic
- Machine Learning in Bioinformatics
- Type
- article
- Field-Weighted Citation Impact
- 4.21