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ML-AdVInfect: A Machine-Learning Based Adenoviral Infection Predictor
(Frontiers, 2021)
Adenoviruses (AdVs) constitute a diverse family with many pathogenic types that infect a broad range of hosts. Understanding the pathogenesis of adenoviral infections is not only clinically relevant but also important to ...
A correlation coefficient-based feature selection approach for virus-host protein-protein interaction prediction
(Plos, 2023)
Prediction of virus-host protein-protein interactions (PPI) is a broad research area where various machine-learning-based classifiers are developed. Transforming biological data into machine-usable features is a preliminary ...
DEVOUR: Deleterious Variants on Uncovered Regions in Whole-Exome Sequencing
(PMC, 2023)
The discovery of low-coverage (i.e. uncovered) regions containing clinically significant variants, especially when they are related to the patient's clinical phenotype, is critical for whole-exome sequencing (WES) based ...