Daniel A. Janies Ph.D.
Associate Professor
phone: (614) 292-1202
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Dr Janies received a B.S. in Biology from the University of Michigan, Ann Arbor, and a Ph.D. in Zoology from the University of Florida, Gainsville. He was a NASA Principal Investigator at the American Museum of Natural History, where previously he had been a Postdoctoral Fellow. Since 2003, Dr Janies has been an Associate Professor at BMI.
Dr. Janies was trained as a biologist, however, as a result of the computational demands of the biological questions he was interested in, he began to develop hardware and software. He led the design, construction, and integration of the parallel computing cluster at the American Museum of Natural History. Using off-the-shelf PC components and relying solely on house talent, his team built an inexpensive, internationally ranked 860-processor supercomputer (see an overview of this work).
Research
Project Involvement
Bioinformatics
My research objectives are to continue to develop computational and evolutionary sciences in a comparative genomics context. I have collaborations with phamacogenomicists and microbiologists. To these ends, I have developed novel phylogenetic methods to correlate genotypes and phenotypes and find diagnostic polymorphisms among organisms. In short, I am mining datasets of mutational history implied by phylogenetic trees for two types of information: 1) recurrent changes in phenotype and genotype among lineages to identify disease candidate genes for complex disease and 2) exclusive changes that are vital to design sensitive reagents such a taxon specific oligonucleotides useful in diagnostics.
Genomics promises a new paradigm for scientific and medical research. Soon we will understand the fundamentals of cellular metabolism, development, and evolution at a basic informational level. This understanding will help us attack the mechanics of the disease rather than treat its symptoms. However having a single genome sequence provides little information by itself. It is through sequence alignment and tree search that one can identify functional regions of bimolecular sequences, diagnose affected from unaffected individuals, and better understand infectious disease. Similarity search is vital to database retrieval, annotation, and gene discovery. Comparative organismal approaches lead to the discovery of the shared functional regions. Thus the field of sequence comparison has much to offer for all fields of modern biology and medicine. Progress requires the synergistic development of software and hardware suited to very large datasets.
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Grant Highlights |
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Publications | click to hide (-) |
Genome Technology cover & article for Dan Janies & team, July/Aug. 2007", July, 2007. " |
Genome Analysis Linking Recent European and African Influenza (H5N1) Viruses", Emerging Infectious Diseases, 13 (5) May, 2007. " |
Genomic Analysis and Geographic Visualization of the Spread of Avian Influenza (H5N1)", Systematic Biology, Vol. 56 (2) : pp. 321-329, May, 2007. " |
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Presentations | click to hide (-) |
Applications of large-scale phylogenetic analysis for research in emerging infectious disease", in Proceedings of 2006 " |
Applications of Large-scale Phylogenetic Analysis for Research In Emerging Infectious Disease", in Proceedings of 2005 " |
Host and Antigenic Evolution of Influenza A as Viewed Through Very Large Datasets", in Proceedings of Fagernes, Norway, 2005 " |
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Tech Reports | click to hide (-) |
POY version 3.0, Documentation and Command Summary, Phylogeny Reconstruction via Direct Optimization of DNA and other data", Technical Report, No. OSUBMI_TR_2002_n03, Biomedical Informatics, 2002. " |
Summary Report of the Workshop on Evolutionary Biology, held at The American Museum of Natural History, NY, March 3-5, 1999", Technical Report, No. OSUBMI_TR_1999_n01, Biomedical Informatics, 1999. " |
MALIGN version 2.7", Technical Report, No. OSUBMI_TR_1998_n01, Biomedical Informatics, 1998. " |
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