A Prediction Model for Membrane Proteins Using Moments Based Features.

Abstract:

:The most expedient unit of the human body is its cell. Encapsulated within the cell are many infinitesimal entities and molecules which are protected by a cell membrane. The proteins that are associated with this lipid based bilayer cell membrane are known as membrane proteins and are considered to play a significant role. These membrane proteins exhibit their effect in cellular activities inside and outside of the cell. According to the scientists in pharmaceutical organizations, these membrane proteins perform key task in drug interactions. In this study, a technique is presented that is based on various computationally intelligent methods used for the prediction of membrane protein without the experimental use of mass spectrometry. Statistical moments were used to extract features and furthermore a Multilayer Neural Network was trained using backpropagation for the prediction of membrane proteins. Results show that the proposed technique performs better than existing methodologies.

journal_name

Biomed Res Int

authors

Butt AH,Khan SA,Jamil H,Rasool N,Khan YD

doi

10.1155/2016/8370132

subject

Has Abstract

pub_date

2016-01-01 00:00:00

pages

8370132

eissn

2314-6133

issn

2314-6141

journal_volume

2016

pub_type

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