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Moore, Jason
University of Pennsylvania
Philadelphia, Pennsylvania
 
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Jason Moore is the Frank Lane Research Scholar in Computational Genetics and Director of Bioinformatics at Dartmouth Medical School, where he holds positions as Associate Professor of Genetics and Adjunct Associate Professor of Community and Family Medicine. He also holds positions as Affiliate Associate Professor of Computer Science at the University of New Hampshire and Adjunct Associate Professor of Computer Science at the University of Vermont. He was previously an Ingram Associate Professor of Cancer Research at Vanderbilt University Medical School, where he held positions as Assistant and Associate Professor of Molecular Physiology and Biophysics. He has won numerous awards including the James V. Neel Young Investigator award from the International Genetic Epidemiology Society and a Best Paper award from the ACM Genetic and Evolutionary Computing Conference (GECCO). He is currently Editor in Chief of a new journal, BioData Mining, that is published by BioMed Central.

Moore is a graduate of the University of Michigan in Ann Arbor, where he earned an MS in Human Genetics, an MA in Applied Statistics, and a PhD in Human Genetics. His dissertation work focused on computational and statistical methods for the genetic analysis of blood pressure change over a 24-hour period. He is also a graduate of Florida State University in Tallahassee, where he earned a BS in Biological Sciences.

His research focuses on the development, evaluation, and application of data mining and machine learning methods for the identification of genetic, genomic, and proteomic predictors of common human diseases, such as cancer and cardiovascular disease. Moore and his team have developed a number of novel machine learning methods, including multifactor dimensionality reduction (MDR) that uses constructive induction to detect nonlinear interactions among two or more attributes. He has published more than 150 peer-reviewed papers in journals and conference proceedings, and has delivered more than 100 invited lectures, including keynote lectures at the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology and the 2006 Annual Conference on the Mathematics of Information Technology and Complex Systems. More information about Moore and his work can be found at www.epistasis.org.

 
 
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   Living cell as a universal computer
Sergienko I., Biletskyy B., Gupal A. Cybernetics and Systems Analysis 49(4): 562-568, 2013.  Type: Article

Computer science has long looked to biology for inspiration in the design of computer systems and software, and the reverse is also true. This paper explores the connection between the biomolecular processes that occur in a cell and th...

Feb 6 2014  
  Prediction of breast cancer using artificial neural networks
Saritas I. Journal of Medical Systems 36(5): 2901-2907, 2012.  Type: Article

The problem of cancer detection and diagnosis is ideally suited for machine learning methods. The goal is to develop a diagnostic model of biological measures extracted from imaging methods, such as mammography, or pathology assays, su...

Jan 23 2013  
  An extended Kalman filtering approach to modeling nonlinear dynamic gene regulatory networks via short gene expression time series
Wang Z., Liu X., Liu Y., Liang J., Vinciotti V. IEEE/ACM Transactions on Computational Biology and Bioinformatics 6(3): 410-419, 2009.  Type: Article

Systems biology is an emerging discipline aimed at understanding how biomolecules interact to influence biological processes such as development, gene regulation, and metabolism. Other disciplines, such as genomics and bioinformatics, ...

Feb 10 2010  
 
 
   
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