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 | | Protein binding | Mathematical models. Proteomics | Mathematical models. Proteins | Metabolism. Peptides | Metabolism. Protein Interaction Mapping.
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|  | A deep learning approach towards protein-peptide binding site prediction
Author: Wardah Wafaa
Institution: The University of the South Pacific
Award: M.Sc.
Subject: Protein binding | Mathematical models. Proteomics | Mathematical models. Proteins | Metabolism. Peptides | Metabolism. Protein Interaction Mapping.
Date: 2019
Call No.: Pac QP 517 .P76 W37 2019
BRN: 1387087
Copyright:Permission to copy work granted.
Abstract: This thesis presents a deep-learning approach for protein-peptide binding site prediction. Proteins are the fundamental components of all living cells and are responsible for most processes that occur in the body. Peptides are smaller molecules comprised of amino acid residues, similar to proteins. Interactions between proteins and peptides influence biological functions.
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