Research Interests

I am interested in bioinformatics, molecular evolution, and molecular population genetics. Owing to many genome projects, almost infinite amount of molecular data is becoming available. They are filled with evolutionary footprints. My interest revolves around mining such information from sequence data, reconstructing the evolutionary process of sequences, genes, and genomes, and applying knowledge we gain from these analyses for protein function prediction and gene mining. Current projects include: 1) development of alignment-free classification methods that can be efficiently and accurately applied to G-protein coupled receptor and other extremely divergent protein superfamily, 2) mining these proteins from diverse genomes, 3) molecular evolutionary analysis of GPCR and other extremely divergent protein superfamily to understand the evolutionary mechanisms of these protein functions, 4) development of sequence simulation methods that incorporate dynamic protein evolution including insertion/deletion, domain structure and shuffling, and 5) improvement of phylogenetic and multiple alignment methods for divergent protein evolution. I am also interested in synonymous codon usage. Although synonymous codon substitutions do not change amino acids, they are not neutral to selection. It makes synonymous codon usage a unique and informative quantity for studying molecular evolution at different levels. One of my goals is to incorporate such information in bioinformatics tools and achieve thorough and multi-dimensional understanding of genomic data.

Recent Publications

• Xia, X., Huang, H., Carullo, M., Betran, E., and Moriyama, E. N. (in press) Conflict between translation initiation and elongation in vertebrate mitochondrial genomes. PLoS ONE
• Strope, P. K. and Moriyama, E. N. (in press) Simple alignment-free methods for protein classification: a case study from G-protein coupled receptors. Genomics
• Strope, C. L., Scott, S. D. and Moriyama, E. N. (2006) indel-Seq-Gen: a new protein family simulator incorporating domains, motifs, and indels. Mol Biol Evol doi: 10.1093/molbev/msl195
• Opiyo, S. O. and Moriyama, E. N. (2007) Protein family classification with partial least squares. J Proteome Res 6: 846-853.
• Moriyama, E. N., Strope, P. K., Opiyo, S. O., Chen, Z. and Jones, A. M. (2006) Mining the Arabidopsis thaliana genome for highly-divergent seven transmembrane receptors. Genome Biology 7: R96.
• Lu, G., Jiang, L., Kotalik, R. M., Rowley, T. W., Zhang, L., Chen, X. J., and Moriyama, E. N. (2006) GenomeBlast: a web tool for small genome comparison. BMC Bioinformatics 7: S18.
• Moriyama, E. N. and J. Kim. (2005) Protein family classification with discriminant function analysis. Pp. 121-132 in Gustafson, J. P., Shoemaker, R. and Snape, J. W. eds. Genome Exploitation: Data Mining the Genome. Springer, New York.
• Simbahan, J., Kurth, E., Schelert, J., Moriyama, E. N., Jovanovich, S. and Blum, P. (2005) Community analysis of a mercury hotspring support domain-specific forms of 3 mercuric reductase. Appl Environ Microbiol 71: 8836-8845.
• Lu, G. and E. N. Moriyama (2004) Vector NTI, a balanced all-in-one sequence analysis suite. Briefings in Bioinformatics 5: 1-11.
• Sainz, A. C., L. V. Mauro, E. N. Moriyama, and B. A. García (2004) Phylogeny of triatomine vectors of Trypanosoma cruzi suggested by mitochondrial DNA sequences. Genetica 121: 229-240.
• Powell, J. R., E. Sezzi, E. N. Moriyama, J. M. Gleason and A. Caccone (2003) Analysis of a shift in codon usage in Drosophila. J Mol Evol, 57: S214-S225.
• Dorer, D.R., J. A. Rudnick, E. N. Moriyama and A. C. Christensen (2003) A family of genes clustered at the Triplo-lethal locus of Drosophila melanogaster has an unusual evolutionary history and significant synteny with Anopheles gambiae. Genetics, 165: 613-621.
• Moriyama, E. N. (2003) Codon Usage. in Cooper, D. N. ed. Nature Encyclopedia of the Human Genome. Nature Publishing Group, Macmillan Publishers Ltd, London.
• Kim, J., E. N. Moriyama, C. G. Warr, P. J. Clyne and J. R. Carlson (2000) Identification of novel multi-transmembrane proteins from genomic databases using quasi-periodic structural properties. Bioinformatics 16: 767-775.