Software Applications in Biomedicine: A Narrative Review of Translational Pathways from Data to Decision

Background/Objectives: Software has become core infrastructure in biomedical science; however, tools and workflows remain fragmented across subfields, limiting reproducibility and slowing translation from data generation to actionable decisions. This narrative review synthesizes representative software ecosystems across three major pillars—bioinformatics, molecular modeling and simulations, and epidemiology/public health—and evaluates their translational readiness using a shared cross-domain framework focused on reproducibility, validation, interoperability, usability, and decision relevance. Methods: A narrative review of articles indexed in PubMed/NCBI, Web of Science, and Scopus between 2000 and 2025 was conducted. Domain-specific terms related to bioinformatics, molecular modeling, docking, molecular dynamics, epidemiology, public health, and workflow management were combined with software- and algorithm-focused keywords. Studies describing, validating, or applying documented tools with biomedical relevance were included. Results: Across domains, mature data standards and reference resources (e.g., FASTQ, BAM/CRAM, VCF, mzML), widely adopted platforms (e.g., BLAST/BLAST+, Bioconductor, AutoDock Vina, GROMACS, Epi Info, QGIS), and increasing use of workflow engines were identified. Software pipelines routinely transform molecular and surveillance data into interpretable features supporting hypothesis generation. Conclusions: Integrated, standards-based, and validated software pipelines can shorten the path from measurement to decision in biomedicine and public health. Future progress depends on reproducibility practices, benchmarking, user-centered design, portable implementations, and responsible deployment of machine learning.