John B. Spalding Adjunct Associate Professor, Molecular Biology spalding@nmsu.edu
BA - Zoology, University of California at Los Angeles MA - Biology, San Francisco State University PhD - Biology, University of New Mexico, 1984	Research Interests Bioinformatics methods for protein fold recognition Bioinformatics applications for protein and DNA sequence analysis

Protein Fold Recognition

The functions of a significant fraction of proteins discovered in genomic and EST studies cannot be deduced from sequence comparisons. An alternative approach is to use fold recognition techniques with these "orphan" proteins to find matches based on predicted structural characteristics. This approach has promise because the number of different folds in the protein universe is very small compared to the number of sequences, indicating that structure is conserved much more than sequence. We have developed a new fold recognition method (Protein Classification through the Assessment of Predicted Secondary Structure or PCAPSS) that builds predicted secondary structure state hidden Markov models of orphan groups and searches the Protein Data Bank (PDB) of experimentally-determined structures. The method focuses on the large number of homologous protein groups identified across many taxa that remain uncharacterized. Working with groups of related sequences improves secondary structure prediction accuracy and facilitates building robust hidden Markov models used to score the PDB. Novel approaches in the method include automated formation of the HMM training set from a single query sequence and the characterization of high-scoring matches by their Structural Classification of Proteins (SCOP) categorizations.

PCAPSS is available as a service on the internet.

Bioinformatics applications for protein and DNA sequence analysis
As Deputy Directory of the Southwest Biotechnology and Informatics Center (SWBIC) I head the Informatics team, which is responsible for computational support for bioinformatics research and education. In this role I am interested in developing bioinformatics tools for myself and the research community. Many of the core algorithms for these tools were derived from the PCAPSS research. These applications are available on the SWBIC Bioinformatics web page and are described there.

Selected Publications

• Spalding, J. B. and Lammers, P. J. 2004. BLAST Filter and GraphAlign: rule-based formation and analysis of sets of related DNA and protein sequences. Nucleic Acids Res. 32: W26-W32.
• Spalding, J. B. and Bernstein, R. L. 2002. Genome Comparisons. Science 297:1037 (Bioinformatics software review)
• Spalding, J. B. 2002. Freedom of Expression. Science 295:153. (Bioinformatics software review)
• Spalding, J. B. 2001. Micro Management. Science 294:629. (Bioinformatics software review)
• Spalding, J. B. 2001. Alignment Formatter. Science 293:715. (Bioinformatics software review)
• Bernstein, R. L. and Spalding, J. B. 2001. Genomic Order. Science 292:1921. (Bioinformatics software review)
• Bernstein, R. L. and Spalding, J. B. 2001. Finding order. Science 292:749. (Bioinformatics software review)
• Lammers, P. J., J. B. Spalding, S. T. Duran, and N. Garcia. 1998. Orphan Protein identification through comparisons of predicted versus experimental secondary structures. Microbial & Comparative Genomics 3, C76-77.
• Taylor, F. and J. B. Spalding. 1988. Timing of diapause in relation to temporally variable catastrophes. J. Evol. Biol. 2:285-298.
• Taylor, F. and J. B. Spalding. 1988. Fitness functions for alternative developmental pathways in the timing of diapause induction. Am. Nat. 5:678-699.
• Taylor, F. and J. B. Spalding. 1986. Geographical patterns in the photoperiodic induction of hibernal diapause. pp. 66-85. In F. Taylor and R. Karban (Eds.) The Evolution of Insect Life Cycles. Springer-Verlag, Berlin, West Germany.
  

Please send comments and suggestions to nancyt@nmsu.edu

Last updated: August 17, 2005