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 for us to analyze. They are filled with evolutionary footprints. My interest revolves around mining such information from sequence data, and reconstructing the evolutionary process of sequences, genes, and genomes.
One of my current interests is directly related to protein functions. It is detecting weak similarities among transmembrane proteins. This is to study how structural and functional constraints have effects on protein sequences, and how we can detect such information. I am developing new methods based on multidimensional classification analyses on a set of physico-chemical properties of amino acid sequences to identify and classify G-protein coupled receptors (this protein super-family includes Acetylcholine receptors, Dopamine receptors etc.). These methods have a potential for identifying other transmembrane proteins and also many other protein families without relying on alignments. It will be useful for functional prediction from ever accumulating genomic data.
Once we detect and identify a set of weakly related proteins, next task is to examine the relationship among these proteins. This is to reconstruct phylogenetic trees based on their amino acid sequences. One particular protein family I am currently interested in is olfactory receptors (this is also a member of the G-protein coupled receptor super-family). I am trying to reconstruct a phylogeny of olfactory and chemo- receptors from diverse groups of organisms (e.g., vertebrates, Drosophila, and C. elegans).
I am also interested in examining more subtle kinds of information that we can gather from genomic data. I am particularly intrigued by the large variation in codon usage pattern observed among different organisms or even among genes in the same organism. Selective constraints on codon usage, bias in mutation pattern and simply random genetic drift, all can contribute to generate a particular codon usage pattern. Therefore, by examining codon usage pattern and comparing it among genes or among organisms, we can obtain information very different from what we gain at the protein sequence level. For example, we can detect a small difference in functional constraints on a particular gene or gene region. We can also speculate population history of the species that can cause the fluctuation in the evolutionary forces. One of my goals is, to incorporate this kind of information in bioinformatics tools and achieve a thorough and multidimensional understanding of genomic data.
Recent Papers
Sainz, A. C., L. V. Mauro, E. N. Moriyama, and B. A. García. in press. Phylogeny of Triatomines (Hemiptera: Reduviidae) suggested by mitochondrial DNA sequences. Genetica.
Dorer, D. R., J. A. Rundnick, 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.
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.
Moriyama, E. N. (2003) Codon Usage. in ENCYCLOPEDIA OF HUMAN GENOME. Macmillan Publishers Ltd, Nature Publishing Group, 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.
BOOK CHAPTERS AND REVIEWS
Moriyama, E. N. (in press) Molecular clock and codon usage bias in Drosophila, in T. Steen, ed. Molecular Clock. University of Chicago Press, Chicago.
Moriyama, E. N. and J. Kim. (in press) Protein family classification with discriminant function analysis. in J. P. Gustafson, ed. Data Mining the Genomes: 23rd Stadler Genetics Symposium. Kluwer Academic/Plenum Publishers, New York
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