Recent increases in the number of genome sequencing projects means that the amount of protein sequence in databases is increasing at an astonishing pace. In proteome studies, this is facilitating the identification of proteins from molecularly well-defined organisms. However, in studies of proteins from the majority of organisms, proteins must be identified by comparing analytical data to sequences in databases from other species. This process is known as cross-species protein identification. Here we present a new program, MultiIdent, which uses multiple protein parameters such as amino acid composition, peptide masses, sequence tags, estimated protein pI and mass, to achieve cross-species protein identification. The program is structured so that protein amino acid composition, which is highly conserved across species boundaries, first generates a set of candidate proteins. These proteins are then queried with other protein parameters such as sequence tags and peptide masses. A final list of database entries which considers all analytical parameters is presented, ranked by an integrated score. We illustrate the power of the approach with the identification of a set of standard proteins, and the identification of proteins from dog heart separated by two-dimensional gel electrophoresis. The MultiIdent program is available on the world-wide web at: http://www.expasy.ch/sprot/multiident.h tml.