Biomedical Informatics is an online multidisciplinary open access journal aiming to provide a peer-reviewed platform for publishing interdisciplinary research that applies software or computational methods to understand living systems at a molecular level through to the cell level.

The topics of interest include, but are not limited to the following:

    Sequence analysis such as sequence assembly, genome annotation, computational evolutionary biology, comparative genomics, genetics of disease, genomics, genome variation, personalized medicines, RNA bioinformatics, and functional consequences of genetic variants
    Gene and protein expression such as analysis of cellular organization, gene and protein expression, computational medicine, transmission dynamics, metagenomics, biomarker discovery, and epigenetics
    Systems biology including metabolic network analysis, translational cell and tissue engineering, biological network analysis, metabolomics, proteomics, structural bioinformatics, network and systems biology, biodiversity informatics, personalized medicines, etc.
    Clinical decision support systems that utilize patient data, medical knowledge, and evidence-based guidelines to provide decision support to healthcare providers in diagnosing diseases, selecting treatment options, and improving patient care outcomes.
    Imaging informatics such as methods for image acquisition, processing, analysis, and interpretation in medical imaging. This includes techniques for image segmentation, registration, feature extraction, and computer-aided diagnosis.
    Method development such as mathematical modeling, machine learning and data mining, biological data integration and management.

Special Issue on Evolutionary Genomics of Host-Pathogen Interactions
截稿日期: 2025-12-01

This special issue aims to explore the dynamic interface where host-pathogen interactions are shaped by evolutionary forces and genomic adaptations. We invite contributions that employ phylogenetic analyses, functional genomics, and evolutionary theory to understand how pathogens evolve alongside their hosts, how these processes influence genomic architecture, and the implications for disease outcomes.

Key topics of interest could include, but are not limited to:

    The use of phylogenetic methods to trace the co-evolution of hosts and pathogens and to infer the evolutionary history of infectious diseases.
    Genomic studies that identify the genetic determinants of pathogenicity and host susceptibility, illuminating the molecular basis of host-pathogen interactions.
    Functional genomic approaches to reveal how gene expression changes during infection can inform on the mechanisms of pathogenic invasion, immune evasion, and host response.
    Evolutionary genomics insights into the development of antimicrobial resistance, and the identification of potential targets for therapeutic intervention.
    Integrative analyses that combine genomic data with other 'omics' to elucidate complex networks involved in host-pathogen dynamics.
    Comparative genomics to understand the conservation and divergence of pathogen strategies across different species or strains and their impact on infection strategies.

We seek original research articles, comprehensive reviews, and thought-provoking perspectives that not only present cutting-edge findings but also synthesize knowledge across disciplines to provide deeper insights into the ongoing battle between pathogens and their hosts. By bringing together works that link phylogenetics, genomics, and functional studies, this special issue will highlight the power of a combined approach to untangling the complexities of infectious diseases.

Special Issue on Single-Cell Multi-Omics
截稿日期: 2025-12-02

Single-cell multi-omics has emerged as a groundbreaking approach to decipher the complex mosaic of cellular heterogeneity and function. Leveraging state-of-the-art low- and high-throughput technologies, researchers are uncovering unprecedented insights into cellular functions, interactions, and regulatory mechanisms. The significance of single-cell multi-omics lies in its ability to delineate the intricate molecular landscapes of complex tissues, fostering more precise diagnostics, targeted therapies, and a deeper comprehension of biological systems.

This special issue aims to consolidate pioneering research that explores comprehensive genomic, transcriptomic, proteomic, epigenomic, and epi-transcriptomic analyses at the single-cell level. The scope of this issue encompasses novel technologies, methodologies, integrative bioinformatics tools, resources, and innovative applications of single-cell multi-omics across various biological contexts.

Topics of Interest Include, but are not limited to:

    New Experimental Technologies for multi-omics data generation
    Computational Methods and Tools for multi-omics data (including machine learning, data integration, statistical models, and data visualization)
    Utilizing Multi-omics Approaches to study development, disease mechanisms, and cellular responses to environmental changes
    Construction of Single-cell Multi-omics data resources and databases
    Single-cell Sequencing-based Multi-omics leveraging advanced technologies such as long-read native sequencing
    Application of Single-cell Multi-omics in clinical studies and personalized medicine, including diagnosis, treatment, and prevention

We invite original research articles, reviews, and technical notes that address the challenges and opportunities in single-cell data integration, analysis, and interpretation.