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

ABSTRACT:

Motivation

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.

Results

We present a comparison of a neural network model versus SVM for prediction of host-pathogen PPI based on a combination of features including: amino acid quadruplets, pairwise sequence similarity, and human interactome properties. The neural network and SVM were implemented using Python Sklearn library. The neural network model using quadruplet features and other network features ou

SUBMITTER: Ahmed I 

PROVIDER: S-EPMC6289132 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature