Research & Reviews: A Journal of Bioinformatics

[2393-8722(e)] is an interdisciplinary peer-reviewed open access journal launched in 2014 serving in fields involving Biology, Computer Science and Statistics. This Journal focuses on the Research, Review works, and recent developments in the area of Bioinformatics, and its applications.

• • Bioinformatic Tools and Sequence Analysis: Sequence alignment and similarity searching, homology detection, sequence profiling, RNA and protein structure prediction, microarray and next-generation sequencing (NGS) analysis, read mapping, virulence and antimicrobial resistance gene prediction.
  • Computational Genomics, Proteomics, and Metabolomics: Genome assembly and annotation, gene function prediction, orthology and pan-genome analysis, genome-wide association studies, SNP analysis, comparative genomic hybridization, gene and protein expression analysis, protein families, motif discovery, proteogenomics, genome evolution.
  • Evolutionary Bioinformatics and Phylogenetic Analysis: Phylogenetic inference and tree visualization, comparative genomics, horizontal gene transfer, gene duplication, speciation, population genetics, DNA barcoding, species and serovar identification, niche modeling.
  • Computational Biology and Systems Biology: Mathematical modeling and simulation, modeling of cell and tissue function, disease gene mapping, epigenomics and gene regulation, transcriptomics, non-coding RNA structure and function, statistical genetics, bioimage analysis, biomedical data privacy.
  • Biological Network Analysis: Interactomes, gene regulatory networks, protein–protein interaction networks, metabolite networks, pathway analysis, network clustering, alignment, visualization, link prediction, perturbation analysis.
  • Integrative Bioinformatics: Data integration and warehousing, metabolic and regulatory network simulation, signaling pathway modeling, integrative data and text mining, Gene Ontology and pathway enrichment profiling, whole-cell modeling.
  • Biomedical Data Engineering, Databases, and Data Mining: Nucleotide, protein, structure, and pathway databases, taxonomic and microbiome data resources, high-throughput and single-cell data analysis, biomedical cloud computing, machine learning for biomedical data, biomedical signal analysis.
  • Biomarker Identification: Computational discovery of predisposition, diagnostic, prognostic, and predictive biomarkers, mass spectrometry–based peptide identification, proteomic biomarker pipelines.
  • Cancer Informatics and Medical Informatics: Multi-omics analysis for cancer detection, classification, and risk prediction, cancer genomic variation, targeted sequencing panels, single-cell cancer genomics, neoantigen prediction, clinical decision support, electronic health records, neuroinformatics, medical image analysis.
  • Molecular Modeling and Dynamics: Homology modeling, receptor modeling and docking, protein–ligand and protein–peptide interactions, de novo ligand design, molecular dynamics and Monte Carlo simulation, molecular mechanics, semi-empirical, ab initio, and post-Hartree–Fock methods, protein folding simulation.
  • Drug Designing: Structure-based and ligand-based drug design, virtual screening, fragment-based design, virtual library design, drug-likeness rules including Lipinski’s rule of five, in silico ADME and toxicity prediction, drug target identification, chemical genomics.
  • In Silico Technology and Synthetic Biology: Chemoinformatics, genetic circuit design, pathway construction, gene optimization, computational protein and metabolic engineering, programmed evolution, synthetic metagenomics, computational analysis of structural biology data.
  • Biological Algorithm and Software Development: Evolutionary and parallel genetic algorithms, swarm intelligence and metaheuristics applied to biological problems, automated machine learning pipelines, bioinformatics software engineering, open-source libraries and workflows in R, Python, and Bioconductor.