Assuming that a significant cause of Parkinson's disease (PD) is genetic, genetic factors have been shown to account for <10% of all PD cases to date, and it is therefore necessary to identify novel genes. The aim of the present study was to identify PD candidate genes using a bioinformatic approach and to screen them for possible PD-causing mutations. The CAESAR (CAndidatE Search And Rank) program was used in the present study to identify and prioritize PD candidate genes. CAESAR ranks annotated human genes as candidates by using ontologies to semantically map natural language descriptions of the trait under investigation to gene-centric databases. Two of the candidates were selected and screened for mutations in 202 South African PD patients using the High-Resolution Melt (HRM) method. Samples exhibiting altered HRM profiles were sequenced. CAESAR generated a prioritized list of candidates including both known and novel PD genes. The MAPT and SNCAIP genes were selected for mutation screening from the list of ten highest scoring genes. Two novel missense (A91V and V635I), four synonymous and three intronic sequence variants were identified in MAPT. For SNCAIP, three novel missense (T383N, R606Q, N906H), one known (E709Q), four synonymous and one intronic sequence variant were found. A bioinformatic approach was used to aid in the identification and selection of PD candidate genes in a group of South African patients. Mutation screening of MAPT and SNCAIP identified novel sequence variants in both genes and further studies are necessary to determine their possible functional consequences.