Cascading classifier application for topology prediction of TMB proteins

Kazemian, Hassan and Grimaldi, Cedric Maxime (2018) Cascading classifier application for topology prediction of TMB proteins. 2018 IEEE Symposium Series on Computational Intelligence (SSCI).

[img]
Preview
Text
Kazemian-Grimaldi-Sep 30th Final.pdf - Accepted Version

Download (371kB) | Preview

Abstract / Description

This paper is concerned with the use of a cascading classifier for trans-membrane beta-barrel topology prediction analysis. Most of novel drug design requires the use of membrane proteins. Trans-membrane proteins have key roles such as active transport across the membrane and signal transduction among other functions. Given their key roles, understanding their structures mechanisms and regulation at the level of molecules with the use of computational modeling is essential. In the field of bioinformatics, many years have been spent on the trans-membrane protein structure prediction focusing on the alpha-helix membrane proteins. Technological developments have been increasingly utilized in order to understand in more details membrane protein function and structure. Various methodologies have been developed for the prediction of TMB proteins topology however the use of cascading classifier has not been fully explored. This research presents a novel approach for TMB topology prediction. The MATLAB computer simulation results show that the proposed methodology predicts transmembrane topologies with high accuracy for randomly selected proteins.

Item Type: Article
Subjects: 000 Computer science, information & general works > 020 Library & information sciences
600 Technology > 610 Medicine & health
Department: School of Computing and Digital Media
Depositing User: Hassan Kazemian
Date Deposited: 03 Dec 2018 09:28
Last Modified: 03 Dec 2018 09:42
URI: http://repository.londonmet.ac.uk/id/eprint/4034

Actions (login required)

View Item View Item