Erica Logan

SNPServer: a real-time SNP discovery tool

SNPServer is a real-time flexible tool for the discovery of SNPs (single nucleotide polymorphisms) within DNA sequence data. The program uses BLAST, to identify related sequences, and CAP3, to cluster and align these sequences. The alignments are parsed to the SNP discovery software autoSNP, a program that detects SNPs and insertion/deletion polymorphisms (indels). Alternatively, lists of related sequences or pre-assembled sequences may be entered for SNP discovery. SNPServer and autoSNP use redundancy to differentiate between candidate SNPs and sequence errors. For each candidate SNP, two measures of confidence are calculated, the redundancy of the polymorphism at a SNP locus and the co-segregation of the candidate SNP with other SNPs in the alignment. SNPServer is available at .

Fuzzy Classification of Secretory Signals in Proteins Encoded by the Plasmodium falciparum Genome

Over five thousand types of protein are produced by the malaria parasite Plasmodium falciparum. Each protein contains the address of a specific destination to which it will be trafficked by various cellular translocation mechanisms. This address may be encoded in a secretory signal, physically represented as an amino acid subsequence forming a motif or pattern. The different signal sequences are classified according to where they occur with respect to the entire amino acid sequence. Biologists are interested in computational techniques that can automatically classify the large amount of data in the Plasmodium falciparum genome, since they have inferred from ongoing experimentation that a correlation exists between particular signals and significant cellular locations. We describe the development of a web-accessible fuzzy classifier of secretory signals in proteins. The application of this classifier to the entire P. falciparum genome immediately produced some biologically-interesting predictions that are briefly discussed.