In this review we will introduce the field of mass informatics, a branch of bioinformatics concerned with the analysis of data from mass spectrometry. As we shall demonstrate, this short definition hides a surprisingly diverse and challenging topic, driven by the remarkable versatility of the mass spectrometer. We first introduce the essential properties of the mass spectrum and highlight its key differences from the more common data types in high‐throughput bioinformatics (sequence, microarray and image data). We then explore the breadth of biochemistry accessible through the associated algorithmic challenge of spectral identification. Finally, we demonstrate instances where data‐mining techniques can be applied to large‐scale spectral libraries, thereby extracting latent biological insight.