Machine learning methods for predicting human-adaptive influenza A virus reassortment based on intersegment constraint.

ABSTRACT:

Introduction

It is not clear about mechanisms underlining the inter-segment reassortment of Influenza A viruses (IAVs).We analyzed the viral nucleotide composition (NC) in coding sequences,examined the intersegment NC correlation, and predicted the IAV reassortment using machine learning (ML) approaches based on viral NC features.

Methods

Unsupervised ML methods were used to examine the NC difference between human-adapted and zoonotic IAVs. Supervised ML models of random forest classifier (rfc) and multiple-layer preceptor (mlp) were developed to predict the human adaption to IAVs.

Results

Our results demonstrated that the frequencies of thymine, cytosine, adenine,and guanine (t, c, a, and g), as well as the content of gc/at were consistently high or low for the segme

SUBMITTER: Zeng DD 

PROVIDER: S-EPMC11970406 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature