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

dc.contributor.authorAhmed, Ibrahim
dc.contributor.authorWitbooi, Peter
dc.contributor.authorChristoffels, Alan
dc.date.accessioned2022-01-11T09:01:31Z
dc.date.available2022-01-11T09:01:31Z
dc.date.issued2018
dc.description.abstractTriplet 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.We present a comparison of a neural network model versus SVM for prediction of hostpathogen 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 outperformance the SVM model. The models are tested against published predictors and then applied to the human-B.anthracis case. Gene ontology term enrichment analysis identifies immunology response and regulation as functions of interacting proteins. For prediction of Human-viral PPI, our model (neural network) is a significant improvement in overall performance compared to a predictor using the triplets feature and achieves a good accuracy in predicting human-B.anthracis PPI.en_US
dc.identifier.citationAhmed, I. et al. (2018). Prediction of human-Bacillus anthracis protein–protein interactions using multi-layer neural network. Bioinformatics, 34(24), 4159-4164. 10.1093/bioinformatics/bty504en_US
dc.identifier.issn1460-2059
dc.identifier.uri10.1093/bioinformatics/bty504
dc.identifier.urihttp://hdl.handle.net/10566/7072
dc.language.isoenen_US
dc.publisherOxford University Pressen_US
dc.subjectHuman-Bacillus anthracisen_US
dc.subjectNeural networken_US
dc.subjectAmino acidsen_US
dc.subjectProteinen_US
dc.subjectBioinformaticsen_US
dc.titlePrediction of human-Bacillus anthracis protein–protein interactions using multi-layer neural networken_US
dc.typeArticleen_US

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