Aim
The Journal of Bioscience and Information Research (JBSIR) aims to provide an interdisciplinary platform for the publication of high-quality original research, review articles, short communications, and innovative studies at the intersection of bioscience, information science, computing, and emerging digital technologies.
The journal seeks to advance scientific knowledge by bringing together researchers working on biological systems and information-based approaches, including artificial intelligence, machine learning, data science, computational modeling, bioinformatics, biological data analysis, and intelligent information systems.
JBSIR encourages research that applies computational and information technologies to address challenges in biology, biotechnology, healthcare, agriculture, environmental science, and related life-science disciplines. The journal also welcomes studies that derive new computational and information-processing approaches inspired by biological systems.
The journal's overall aim is to promote interdisciplinary collaboration and facilitate the development of innovative methods, technologies, and applications that contribute to both bioscience and information research.
Scope
The scope of JBSIR includes, but is not limited to, the following areas:
1. Bioscience and Biological Sciences
Molecular biology
Cell biology
Microbiology
Genetics and genomics
Biochemistry
Biotechnology
Plant and animal sciences
Ecology and environmental biology
Evolutionary biology
Immunology
Neuroscience
Developmental biology
Biomedical and life-science research
2. Bioinformatics and Computational Biology
Bioinformatics
Computational biology
Genomic and proteomic data analysis
Sequence analysis
Structural bioinformatics
Systems biology
Computational genomics
Biological network analysis
Biological databases and knowledge systems
Computational modeling of biological systems
3. Artificial Intelligence and Machine Learning in Bioscience
Machine learning for biological applications
Deep learning in bioscience
Artificial intelligence in healthcare and life sciences
Intelligent diagnosis and prediction systems
Pattern recognition in biological data
Computer vision for biological and biomedical applications
Explainable and trustworthy AI for bioscience
AI-assisted biological discovery
4. Biological Data Science and Information Systems
Biological and biomedical data analytics
Big data in bioscience
Data mining for biological applications
Biological information systems
Data management and integration
Knowledge representation and discovery
Biological databases
Cloud and distributed computing for bioscience
Internet of Things (IoT) applications in biological and environmental monitoring
5. Digital Health and Biomedical Information
Health information systems
Medical and biomedical data analytics
Digital health technologies
Clinical decision-support systems
Intelligent healthcare systems
Medical informatics
Biomedical image and signal analysis
Remote and intelligent health monitoring
Wearable and sensor-based health technologies
6. Biotechnology and Computational Technologies
Computational biotechnology
Bioengineering and biological systems
Bioprocess modeling and optimization
Computational approaches to drug and biomolecule discovery
Protein and enzyme analysis
Synthetic biology and information technologies
Biosensors and intelligent sensing systems
Computational approaches to agricultural biotechnology
7. Environmental and Agricultural Information Research
Environmental data science
Computational ecology
Precision agriculture
Smart agriculture
Agricultural informatics
Remote sensing for biological and environmental applications
Intelligent environmental monitoring
Climate and ecosystem data analysis
Biodiversity informatics
8. Emerging and Interdisciplinary Areas
Biological information processing
Nature-inspired computing
Artificial life and bio-inspired computation
Biological networks and complex systems
Digital twins for biological systems
Computational approaches to sustainability
Human–technology interaction in health and bioscience
Emerging technologies with applications in life sciences
JBSIR welcomes original research articles, review articles, systematic reviews, short communications, technical papers, and other scholarly contributions that make a clear scientific contribution to bioscience or information research.
The journal particularly encourages interdisciplinary studies that integrate biological knowledge with computational, mathematical, engineering, and information-science methodologies. Studies should demonstrate scientific rigor, methodological clarity, and relevance to the advancement of knowledge or practical applications.
Research involving data, software, computational models, or artificial intelligence is encouraged to provide sufficient methodological information to support transparency, reproducibility, and, where appropriate, reuse of research outputs.
