The terms bioinformatics and computational biology are often used interchangeably, although the former typically focuses on algorithm development and specific computational methods, while the latter focuses more on hypothesis testing and discovery in the biological domain. Although this distinction is used by National Institutes of Health in their working definitions of Bioinformatics and Computational Biology, it is clear that there is a tight coupling of developments and knowledge between the more hypothesis-driven research in computational biology and technique-driven research in bioinformatics. Computational biology also includes lesser known but equally important subdisciplines such as computational biochemistry and computational biophysics.

A common thread in projects in bioinformatics and computational biology is the use of mathematical tools to extract useful information from noisy data produced by high-throughput biological techniques such as genomics (The field of data mining overlaps with computational biology in this regard). A representative problem in bioinformatics is the assembly of high-quality DNA sequences from fragmentary "shotgun" DNA sequencing, while in computational biology, a representative problem might be statistical testing of a hypothesis of common gene regulation using data from mRNA microarrays or mass spectrometry.