alexa James Lyons Weiler | Bioinformatics Analysis Core Unive
ISSN: 2153-0602

Journal of Data Mining in Genomics & Proteomics
Open Access

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James Lyons Weiler

James Lyons Weiler James Lyons-Weiler
Director
Bioinformatics Analysis Core
University of Pittsburgh
USA
Biography

Dr. Lyons Weiler is a Senior Research Scientist at the University of Pittsburgh where he is the Scientific Director of the Bioinformatics Analysis Core. He earned his PhD at University of Nevada Reno in Ecology Evolution and Conservation Biology. He has published numerous papers with advanced novel methods for genomic proteomic and integromic data analysis. He has taught genetics, population genetics, biology, evolutionary biology, bioinformatics and clinical research principles. He served as the founding Editor in Chief of Cancer Informatics. He serves as a reviewer of peerreviewed journals in the areas of genomics proteomics bioinformatics and clinical decision analysis. He has organized regional and national meetings in bioinformatics. He was the recipient of the Sloan/US DOE Postdoctoral Award in Computational Molecular Biology under the tutelage of Dr Masatoshi Nei and Web Miller at the Pennsylvania State University

Research Interest

Past research areas have included the development of novel paradigms for identifying differentially expressed genes in cancers, methods design to optimize the application of methods of high-dimensional data analysis at small sample numbers, development of new methods for machine learning survival analysis, and the development of entirely new paradigm for integrative translational and clinical research. Current research foci include the automation of methods evaluation and selection for high-dimensional data analysis, comparative evaluation of case/control selection methods via multivariate balancing, optimization of mass spectrometry peptide identification via consensus of search engines, development of generalizable survivorship prediction models via machine-learning, and a comprehensive scoring function for lead identification in next generation sequencing studies.

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