The Journal of Bioinformatics (JOB) publishes high-quality original research articles, reviews, short communications, case studies, and technical perspectives that explore every aspect of computational biology, data-driven life science research, and emerging bioinformatics technologies. We welcome submissions across a diverse range of thematic areas, including (but not limited to):

Genomics, Transcriptomics & Systems Biology

• Genome sequencing, assembly, and annotation
• Transcriptome analysis, RNA-seq pipelines, and gene expression profiling
• Gene regulatory networks, pathway analysis, and systems biology modeling
•  Multi-omics integration and high-throughput data interpretation

Proteomics, Metabolomics & Structural Bioinformatics

•  Protein structure prediction, modeling, and molecular interactions
•  Mass spectrometry-based proteomics and metabolomics data analysis
• Computational analysis of post-translational modifications
•  Structural databases, docking, and virtual screening workflows

Computational Biology & Algorithm Development

• · Machine learning and AI methodologies for biological data
• · Novel algorithms for sequence analysis, alignment, and phylogenetics
• · Network biology, graph-based modeling, and evolutionary computation
• · Big-data analytics, optimization techniques, and scalable bioinformatics tools

Biomedical Informatics & Precision Medicine

•  Clinical data mining, electronic health records, and disease modeling
•  Computational drug discovery, target prediction, and repurposing approaches
•  Personalized medicine, pharmacogenomics, and biomarker identification
•  Integration of clinical, genomic, and imaging data for predictive diagnostics

Molecular Modeling, Simulation & Computational Chemistry

•  Molecular dynamics simulations and quantum chemical calculations
•  Docking, ligand–receptor interactions, and binding free-energy estimation
•  Chemical informatics, QSAR/QSPR modeling, and compound screening
• AI-assisted molecular design and virtual library generation

Data Science, AI & Bioinformatics Software Development

•  Deep learning, neural networks, and generative models for biology
• Development of bioinformatics tools, pipelines, databases, and platforms
• Cloud computing, HPC, and scalable architectures for big biological data
•  Data visualization, workflow automation, and reproducible research frameworks

Microbiome, Evolutionary Biology & Environmental Bioinformatics

• · Metagenomics, microbial community analysis, and microbiome–host interactions
• · Comparative genomics, evolutionary modeling, and phylogenetic reconstruction
• · Environmental sequencing, biodiversity informatics, and ecosystem analysis
• · Microbial functional profiling and ecological network modeling

Ethical, Educational & Emerging Dimensions in Bioinformatics

•  Data privacy, ethical considerations, and responsible AI in biology
•  Training, pedagogy, and curriculum development in bioinformatics
• Open science, FAIR data principles, and reproducibility standards
•  Future directions in bioinformatics and interdisciplinary innovation