학술논문
Implementation of Data Mining Tools to Classify Protein Structural Class from Residue Based Averaged NMR Chemical Shifts
Document Type
Conference
Author
Source
2021 International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA) Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA), 2021 International Conference on. :1-4 Oct, 2021
Subject
Language
Abstract
To understand function of proteins in living bodies we need to derive the protein sequences genome sequencing projects. For this purpose, we can use various tools or latest computational methods. These methods are related to the functions directly. Nuclear magnetic resonance (NMR) is helpful to make the 3 D protein structure. We’re using a unique method to determine the protein structures in this paper. 1491 proteins have been taken in consideration from BMRB - Biological Magnetic Resonance Bank. The structural categorization of proteins (SCOP) method was useful in locating a set of 119 traits divided into 5 separate types. After conducting study, we were able to determine the structural classes of proteins with an accuracy of 80%. taking help of using Matthew Correlation coefficient. Results conclude that we can use NMR-based method for protein structural class identification as a tool for low-resolution.