Work

Surface Glycoprotein Classification Using Repeat Sequences

Year: 2025

Type: article

Abstract: Correct recognition of sequence characteristics is one of the most important steps in bioinformatics. The paper presents a method for the characterization of surface glycoprotein in different viruses. The method uses amino-acid and nucleotide repeat sequences to form a virus/protein profile that is used to characterize and predict the type of protein. Based on a set of characteristic repetitive sequences, a classification model for predicting the type of virus was constructed.

Source: IPSI Transactions on Internet Research

DOI: 10.58245/ipsi.tir.2502.10

Authors: Samira Alshafah, Miloš Beljanski, Nenad Mitić

Institutions: Al Zawiya University, Institute of General and Physical Chemistry, University of Belgrade

Language: English

Topic: Machine Learning in Bioinformatics

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: bronze

OpenAlex ID: W4410885607

FWCI:

Cites: 11

Cited by:

Related to: 10