Prediction of human-Bacillus anthracis protein–protein interactions using multi-layer neural network | Zendy

Ahmed Ibrahim | Zendy; Peter J. Witbooi | Zendy; Alan Christoffels | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Prediction of human-Bacillus anthracis protein–protein interactions using multi-layer neural network

Author(s) -

Ahmed Ibrahim,

Peter J. Witbooi,

Alan Christoffels

Publication year - 2018

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bty504

Subject(s) - artificial intelligence , computer science , feature selection , artificial neural network , machine learning , support vector machine , bacillus anthracis , pairwise comparison , computational biology , pattern recognition (psychology) , biology , genetics , bacteria

Triplet amino acids have successfully been included in feature selection to predict human-HPV protein-protein interactions (PPI). The utility of supervised learning methods is curtailed due to experimental data not being available in sufficient quantities. Improvements in machine learning techniques and features selection will enhance the study of PPI between host and pathogen.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research