About the Journal

Research Spectrum: Bioinformatics in Research and Practice is a peer-reviewed journal dedicated to publishing high-quality research articles, reviews, and selected high-impact reprints that advance research and education at the intersection of computational science, biology, and medicine. The journal emphasizes innovative computational methods and analytical approaches that extract meaningful insights from biomedical data, transforming it into actionable knowledge. By promoting data-driven solutions, the journal supports the development of computational workflows, analytical tools, and methodologies that address complex biomedical problems and enable translational research.

Published tri-annually, the journal is available in both print and electronic formats, ensuring wide accessibility to the research community.​

Scope:

The journal welcomes high-quality submissions in all aspects of bioinformatics, clinical informatics, imaging informatics, public health informatics, computational biology and medicine, pharmacological data science, and methodological innovations that advance the analysis and interpretation of biomedical data. Areas of interest include, but are not limited to:

  • Bioinformatics – Genome and sequence analysis, gene/protein expression, comparative and functional genomics, protein dynamics, data mining, AI/machine learning, network analysis, translational informatics
  • Clinical Informatics – Clinical applications, system design, clinical big data, genomics/omics integration, clinical trial informatics
  • Imaging Informatics – PACS, radiology information systems, computer-aided diagnosis, 3D tissue visualization, functional imaging, AI in medical imaging
  • Public Health Informatics – Consumer health informatics, hospital/healthcare records, national registries, electronic medical records
  • Computational Biology & Medicine – Data-analytical methods, mathematical modelling, simulation techniques, systems biology
  • Pharmacological Data Science – Computational pharmacometrics, systems pharmacology, computer-aided drug discovery, omics-driven drug development
  • Methodological Papers – Classification, clustering, pattern recognition, complex data modelling, knowledge discovery in biomedical datasets