The Journal of Biology and Biological Chemistry is a peer-reviewed scientific publication dedicated to advancing high-quality research at the intersection of computational sciences, biology, and chemistry. Serving as a dynamic interdisciplinary platform, the journal brings together researchers, academics, and industry professionals to disseminate innovative scientific discoveries, methodological breakthroughs, and emerging technological developments across the rapidly evolving fields of computational biology, computational chemistry, and related disciplines.

The journal invites original research that unites computational, theoretical, and data-driven strategies to solve pressing problems in biology and chemistry. Priority areas encompass Biology, Computational Chemistry, Computational Biology, Bioinformatics, Quantum Chemistry, Computer-Aided Drug Design (CADD) and Drug Discovery, Molecular Modelling, Cheminformatics, Theoretical Chemistry, and computation-driven engineering applications.

Aims and Scope

 

The journal publishes original research articles, comprehensive reviews, short communications, and methodological notes covering a broad spectrum of topics, including but not limited to:

 

Biology - Systems Biology, Structural Biology, Genomics, Transcriptomics, Proteomics, Metabolomics, Phylogenetics, Population Genetics, Ecological Modelling, Plant Breeding, Plant Genetics, Biotechnology and Synthetic Biology.  

Bioinformatics and Genomics – sequence analysis, genome annotation, comparative genomics, and metagenomics.

Structural Bioinformatics – protein structure prediction, molecular docking, and structure function relationships.

Computational Chemistry – quantum chemistry, molecular modeling, and cheminformatics.

Computational Biology - Molecular docking, molecular dynamics, drug design.

Systems Biology – network modeling, pathway analysis, and multi omics integration.

Computer Aided Drug Design (CADD), and Discovery- Computer Aided Drug Design (CADD), and Discovery.

Machine Learning and Artificial Intelligence – AI driven drug discovery, predictive modeling, and pattern recognition in biological data.

Biostatistics and Data Science – statistical methods for high throughput biological data.

Pharmacoinformatics – virtual screening, ADMET prediction, and rational drug design.

Molecular Dynamics – simulations of biomolecular systems, protein ligand interactions, and conformational dynamics.

Evolutionary Biology – phylogenetic analysis, molecular evolution, and population genetics.