James Lyons-Weiler, Associate Professor
PhD
Department of Biomedical Informatics
Email: lyonsweilerj@upmc.edu
Research Interest:
Dr. Lyons-Weiler's research interests are in (1) optimization of disease prediction modeling in cancer and other diseases, including genetic, genomic and proteomic biomarkers for early detection and therapy response prediction; (2) optimization of survivorship prediction models; (3) decision modeling to optimize the integration of new clinical options into existing clinical workflows and strategies.
Recent Publication
Patel, S., J. Lyons-Weiler. 2004. caGEDA: A web application for the integrated analysis of global gene expression patterns in cancer. Applied Bioinformatics 3:49-62.
Hauskrecht, M., R. Pelikan, D. Malehorn, W.L. Bigbee, M.T. Lotze, H.J. Zeh, III, D.C. Whitcomb, and J. Lyons-Weiler. 2005. Feature Selection for Classification of SELDI-TOF-MS Proteomic Profiles. Applied Bioinformatics 4:227-46.
Lyons-Weiler, J., S. Patel, M.J. Becich and T. Godfrey. 2004. Tests for finding complex patterns of differential expression in cancer: towards individualized medicine. BMC Bioinformatics, 5:110.
Lyons-Weiler, J., S. Patel and S. Bhattacharya. 2003. A classification-based machine learning approach for the analysis of genome-wide expression data. Genome Research 13:503-512.
Liqiang X., J. Lyons-Weiler, M.C. Coello, X. Huang, W.E. Gooding, J.D. Luketich, T.E. Godfrey. 2005 Prediction of lymph node metastasis by analysis of gene expression profiles in primary lung adenocarcinomas. Clinical Cancer Research 11:1099-109.
Bhattacharya, S., D. Long, J. Lyons-Weiler. 2004. Overcoming confounded controls in the analysis of gene expression data from microarray experiments. Applied Bioinformatics 2:197-208.
