Use of Bioinformatics in Clinical Diagnosis: A Review

The application of bioinformatics in veterinary medicine has transformed clinical diagnosis by enabling data-driven molecular characterization of disease across companion and production animals. This systematic review critically evaluates peer-reviewed literature on bioinformatic approaches used in veterinary clinical diagnostics, with emphasis on comparative oncology, infectious disease genomics, pharmacogenomics, and One Health applications. Relevant studies published over the last decade were identified through structured database searches and assessed for methodological rigor and diagnostic relevance. Evidence indicates that next-generation sequencing and multi-omics analyses significantly improve detection of pathogenic variants and infectious agents in animals, particularly in canine oncology where genomically matched therapies are associated with improved clinical outcomes. Metagenomic sequencing has enhanced identification of zoonotic pathogens, although accurate interpretation depends on robust bioinformatic filtering pipelines. Pharmacogenomic screening, exemplified by routine genotyping of the canine ABCB1 mutation, has demonstrably reduced adverse drug reactions in susceptible breeds. Despite these advances, challenges remain in reference genome completeness, data interpretation, and integration of multi-omic datasets. Overall, this review highlights the growing clinical impact of bioinformatics in veterinary diagnostics and its critical role within the One Health framework.