Generic model to unravel the deeper insights of viral infections: an empirical application of evolutionary graph coloring in computational network biology

Purpose Graph coloring approach has emerged as a valuable problem-solving tool for both theoretical and practical aspects across various scientific disciplines, including biology. In this study, we demonstrate the graph coloring’s effectiveness in computational network biology, more precisely in ana...

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Bibliographic Details
Published in:	BMC bioinformatics Vol. 25; no. 1; pp. 74 - 33
Main Authors:	Kole, Arnab, Bag, Arup Kumar, Pal, Anindya Jyoti, De, Debashis
Format:	Journal Article
Language:	English
Published:	London BioMed Central 16.02.2024 BioMed Central Ltd Springer Nature B.V BMC
Subjects:	Algorithms Bioinformatics Biological activity Biology Biomarkers Biomedical and Life Sciences Computational biology Computational Biology/Bioinformatics Computational neuroscience Computer Appl. in Life Sciences Cough COVID-19 Differential evolution Disease transmission DNA binding proteins Drug target Drugs Effectiveness Empirical analysis Epidemics Evolutionary computation Gene regulation Generic model Genetic transcription Graph coloring Graph theory Health aspects Hub proteins Identification India Infection Infections KEGG pathway Life Sciences Localization Medical research Medicine, Experimental Microarrays Neural networks Optimization Pandemics Pathophysiology Problem solving Protein-protein interactions Proteins Protein–protein interaction networks Respiratory diseases Severe acute respiratory syndrome coronavirus 2 Signs and symptoms Therapeutic targets Transcription factors Viral diseases Viral infections Virus research Viruses India Protein–protein interaction networks Hub proteins KEGG pathway Differential evolution Drug target Generic model Respiratory disorder
ISSN:	1471-2105, 1471-2105
Online Access:	Get full text
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