Kumar, Vinod and Kumar, Rajesh and Agrawal, Piyush and Patiyal, Sumeet and Raghava, G.P.S. (2020) A Method for Predicting Hemolytic Potency of Chemically Modified Peptides From Its Structure. Frontiers in pharmacology, 11. ISSN 1663-9812
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In the present study, a systematic effort has been made to predict the hemolytic potency of chemically modified peptides. All models have been trained, tested, and evaluated on a dataset that contains 583 modified hemolytic peptides and a balanced number of non-hemolytic peptides. Machine learning techniques have been used to build the classification models using an immense range of peptide features that include 2D, 3D descriptors, fingerprints, atom, and diatom compositions. Random Forest based model developed using fingerprints as an input feature achieved maximum accuracy of 78.33% with AUC of 0.86 on the main dataset and accuracy of 78.29% with AUC of 0.85 on the validation dataset. Models developed in this study have been incorporated in a web server "HemoPImod" to facilitate the scientific community (http://webs.iiitd.edu.in/raghava/hemopimod/).
| Item Type: | Article |
|---|---|
| Additional Information: | Copyright of this article belongs to Frontiers Media SA. |
| Uncontrolled Keywords: | modified hemolytic peptides, machine learning, chemical descriptors, fingerprints, random forest, HemoPImod |
| Subjects: | Q Science > QR Microbiology |
| Depositing User: | Dr. K.P.S.Sengar |
| Date Deposited: | 01 May 2020 14:21 |
| Last Modified: | 01 May 2020 14:21 |
| URI: | http://crdd.osdd.net/open/id/eprint/2566 |
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