Pulsed-field gel electrophoresis (PFGE) and multiple-locus variable-number tandem-repeat analysis (MLVA) are used to assess genetic similarity between bacterial strains. There are cases, however, when neither of these methods quantifies genetic variation at a level of resolution that is well suited for studying the molecular epidemiology of bacterial pathogens. To improve estimates based on these methods, we propose a fusion algorithm that combines the information obtained from both PFGE and MLVA assays to assess epidemiological relationships. This involves generating distance matrices for PFGE data (Dice coefficients) and MLVA data (single-step stepwise-mutation model) and modifying the relative distances using the two different data types. We applied the algorithm to a set of Salmonella enterica serovar Typhimurium isolates collected from a wide range of sampling dates, locations, and host species. All three classification methods (PFGE only, MLVA only, and fusion) produced a similar pattern of clustering relative to groupings of common phage types, with the fusion results being slightly better. We then examined a group of serovar Newport isolates collected over a limited geographic and temporal scale and showed that the fusion of PFGE and MLVA data produced the best discrimination of isolates relative to a collection site (farm). Our analysis shows that the fusion of PFGE and MLVA data provides an improved ability to discriminate epidemiologically related isolates but provides only minor improvement in the discrimination of less related isolates.Salmonellosis is one of the most common food-borne diseases in the United States (5). Consequently, it is important to understand how Salmonella strains disseminate within and between reservoirs and environments. Many molecular typing tools have been used for this purpose (11). Of these methods, pulsed-field gel electrophoresis (PFGE) is considered by many to be the gold standard for strain typing, and variable-number tandem-repeat (VNTR) assays are powerful alternative or complementary typing tools (3,22). Both methods offer a high degree of genetic resolution for strain typing, depending on several factors.PFGE involves separating chromosomal DNA macro-restriction fragments by size, and strains are discriminated based on the resulting band pattern observed after electrophoresis has been completed. It is one of the most reproducible and highly discriminatory typing techniques and has been widely and successfully used for a variety of Salmonella enterica serovars (12, 15); for many situations, PFGE is capable of discriminating between closely related strains. In addition, the use of the assay to analyze different serovars does not require a great deal of modification, as might be required with procedures that are dependent on PCR. Difficulties arise when strains are very closely related (i.e., poor discrimination [18,27]) or when bands comigrate in the gel or identically sized bands represent completely different fragments of chromosomal DNA and thereby produce spurio...