| ICGI 2002 |
Amsterdam September 23-25th |
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Skip Garner
Biomedical applications of text data mining and applied computational genomic analysis.
Abstract:
With the "completion" of the first genome, the daily analysis of genomic variation and gene expression, and new technologies amassing proteome data, the need for computational tools, inspired by biomedical insight and need are being developed by many groups to help scientists reduce this data to knowledge. To attain understanding from this data, several things are now required for progress; applied computational tools, access to phenotype presenting patients/biological material (and their genotype), and experts to assimilate this information. In this talk, I will describe efforts within our laboratory to develop and then validate some applied computational tools that are then used by our expert collaborators and us. These include: 1) Techniques and applications to better identify information in text databases, focusing on two example codes, eTBLAST, a text document retrieval system and IRIDESCENT, a knowledge discovery/hypothesis generation system; 2) Computer algorithms and codes that inspect the genome (coding and intronic) for highly probable genetic variations leading to disease; 3) Software to integrate data from some of the many valuable public databases with experimental data, and 4) Software to do integrated analysis and interactive visualization of genomic sequence data.
Each of our software applications is applied to biomedical problems to validate their utility and verify their accuracy, which can only be done by returning to the wet laboratory. The biomedical areas under investigation include cancer, cardiac disease, development, biothreat agents, inflammation and infection. This approach has led to gene discoveries, phenotype causing gene variations and has inspired research directions for which the final answer is not yet in. This presentation will focus on our applied computational tools and the biomedical observations made with them and touch on how some of the associated biomedical technologies have accelerated that process.
Much of the software and databases we develop are available for public use via our www site at http://innovation.swmed.edu/. This work is supported by the NIH, the State of Texas and the P.O'B. Montgomery Distinguished Chair.
This talk represents research by
Harold "Skip" Garner, Jonathan Wren, Alexander Pertsemlidis,
and other members
of the lab and collaborators, at
McDermott Center for Human Growth and Development and the Center for
Biomedical Inventions, UT Southwestern Medical Center, 5323 Harry Hines
Blvd., Dallas, Texas, 75390-8591.
For more information, contact Skip Garner at
garner@swmed.edu.
Keywords: bioinformatics, text data mining, prediction, genetic disease