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The development of gene microarrays are expected to advance cancer diagnosis and treatment. Gene microarrays are silicon chips or membranes imprinted with DNA or its segments that allow study of the interaction among thousands of genes at once by analyzing their expression patterns. ECE’s Yue Wang (Joseph) heads a $5 million effort to use microarrays in developing bioinformatics tools to for cancer research.
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Yue Wang (Joseph) leads a team that was recently awarded two multi-year grants totaling $2.5 million to pursue advances in bioinformatics tools to improve breast cancer diagnosis and therapy. The grants, which start this year, are in addition to about $3 million in ongoing funding for similar objectives.
The team is working to develop the “smart” algorithms and in-silicon experiments that will help characterize and analyze the molecular signature of individual patient’s tumors so that appropriate therapy can be targeted with improved outcomes.
Members of the multidisciplinary investigating team include researchers from Georgetown University, The Catholic University of America, the National Cancer Institute, and Johns Hopkins University.
A grant on “Molecular Analysis of Breast Cancer” from the National Institutes of Health and the Department of Defense will fund work on defining the gene expression profiles of 600 invasive breast tumors, then building integrative intelligence-based multivariate classifiers to predict patients with cancer that will not recur.
A grant on “Comprehensive Analysis of Microarray Gene Expression Data” from the National Cancer Institute of the National Institutes of Health is to interpret information from gene microarray data so that tumors can be classified at the molecular level and response to therapy can be predicted. Gene microarrays are silicon chips or nylon membranes imprinted with DNA or its segments that allow researchers to study the interaction among thousands of genes at once by analyzing their expression patterns.
The team is relying on state-of-the-art technology in engineering, computer science, advanced statistics, and neural networks. The bioinformatics efforts include establishing a database of gene expression profiles, extracting and refining most relevant biomarkers for the various cancer phenotypes, and developing, optimizing and validating neural network classifiers to predict tumor phenotype and response to therapy with confidence values.
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