Bioinformatics

Definition

The interdisciplinary science of developing and applying computational methods, algorithms, and software tools to collect, store, analyze, and interpret biological data, particularly large and complex datasets such as genomic sequences, transcriptomes, proteomes, and ecological inventories. Bioinformatics integrates biology, computer science, mathematics, and statistics to extract patterns, infer evolutionary relationships, predict molecular structures, and model biological processes. In natural history contexts, it enables phylogenomic reconstruction, population genetic analysis, barcode-based species identification, and the mining of biodiversity databases.

Etymology

From Greek bios (life) + information + -ics (field of study); coined in the 1970s to describe the application of information theory to biological systems, later expanding to encompass computational analysis of molecular data.

Example

Researchers used bioinformatics pipelines to assemble and annotate the genome of the monarch butterfly Danaus plexippus, identifying genes involved in migratory behavior and cardenolide detoxification; similarly, metabarcoding studies rely on bioinformatics to process millions of DNA sequences from arthropod community samples and assign them to operational taxonomic units.

Synonyms

• computational biology (disputed, often used interchangeably though some distinguish bioinformatics as data analysis versus computational biology as model-building)

Related Terms

• Genomics
• transcriptomics
• phylogenomics
• metabarcoding
• computational biology
• molecular systematics
• biodiversity informatics
• DNA barcoding
• Proteomics
• population genetics

Usage Notes

The distinction between bioinformatics and computational biology is contested: bioinformatics traditionally emphasizes data management, algorithm development, and large-scale sequence analysis, while computational biology focuses on mathematical modeling of biological systems. In practice, the terms overlap heavily. Bioinformatics is essential to modern taxonomy (phylogenomics), disease ecology (pathogen genomics), and conservation (population genetic monitoring), though it is not itself a field method—rather, it supports downstream analysis of specimens and samples collected in the field. Specialists may distinguish 'dry lab' bioinformatics from 'wet lab' molecular biology.