What is bioinformatics?

Put simply, bioinformatics is the science of storing, retrieving and analysing large amounts of biological information. It is a highly interdisciplinary field involving many different types of specialists, including biologists, molecular life scientists, computer scientists and mathematicians.

Historically, the term bioinformatics was frequently used to describe the analysis of DNA and protein sequence data. Whilst these methods are fundamental to many large-scale experiments in the molecular life sciences, nowadays bioinformatics is considered to be a much broader discipline, encompassing modelling and image analysis in addition to the classical methods used for comparison of linear sequences or three-dimensional structures (Figure 1).

A broad overview of the different types of data that fall within the scope of bioinformatics

Figure 1 A broad overview of the different types of data that fall within the scope of bioinformatics. Traditionally, bioinformatics was used to describe the science of storing and analysing biomolecular sequence data, but the term is now used much more broadly, encompassing computational structural biology, chemical biology and systems biology (both data integration and the modelling of systems).

What bioinformatics is not

Bioinformatics is distinct from medical informatics – the interdisciplinary study of the design, development, adoption and application of IT-based innovations in healthcare services delivery, management and planning. Somewhere in between the two disciplines lies biomedical informatics – the interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific enquiry, problem solving and decision making, motivated by efforts to improve human health.

Recently initiated projects, such as the 100,000 Genomes Project, are bridging the gaps between these disciplines, but on the whole bioinformatics deals with research data and uses it for research purposes, medical informatics deals with data from individual patients for the purposes of clinical management, (diagnosis, treatment, prevention...) and biomedical informatics attempts to bridge these two extremes.