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Life Sciences

Selected Works

Jeffrey S. Morris

Articles 1 - 3 of 3

Full-Text Articles in Physical Sciences and Mathematics

Statistical Contributions To Bioinformatics: Design, Modeling, Structure Learning, And Integration, Jeffrey S. Morris, Veera Baladandayuthapani Dec 2016

Statistical Contributions To Bioinformatics: Design, Modeling, Structure Learning, And Integration, Jeffrey S. Morris, Veera Baladandayuthapani

Jeffrey S. Morris

The advent of high-throughput multi-platform genomics technologies providing whole-genome molecular summaries of biological samples has revolutionalized biomedical research. These technologies yield highly structured big data, whose analysis poses significant quantitative challenges. The field of Bioinformatics has emerged to deal with these challenges, and is comprised of many quantitative and biological scientists working together to eectively process these data and extract the treasure trove of information they contain. Statisticians, with their deep understanding of variability and uncertainty quantification, play a key role in these efforts. In this article, we attempt to summarize some of the key contributions of statisticians to bioinformatics, …

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Bayesian Methods For Expression-Based Integration, Elizabeth M. Jennings, Jeffrey S. Morris, Raymond J. Carroll, Ganiraju C. Manyam, Veera Baladandayuthapani Dec 2012

Bayesian Methods For Expression-Based Integration, Elizabeth M. Jennings, Jeffrey S. Morris, Raymond J. Carroll, Ganiraju C. Manyam, Veera Baladandayuthapani

Jeffrey S. Morris

We propose methods to integrate data across several genomic platforms using a hierarchical Bayesian analysis framework that incorporates the biological relationships among the platforms to identify genes whose expression is related to clinical outcomes in cancer. This integrated approach combines information across all platforms, leading to increased statistical power in finding these predictive genes, and further provides mechanistic information about the manner in which the gene affects the outcome. We demonstrate the advantages of the shrinkage estimation used by this approach through a simulation, and finally, we apply our method to a Glioblastoma Multiforme dataset and identify several genes potentially …

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The Importance Of Experimental Design In Proteomic Mass Spectrometry Experiments: Some Cautionary Tales, Jeffrey S. Morris, Jianhua Hu, Kevin R. Coombes, Keith A. Baggerly Mar 2005

The Importance Of Experimental Design In Proteomic Mass Spectrometry Experiments: Some Cautionary Tales, Jeffrey S. Morris, Jianhua Hu, Kevin R. Coombes, Keith A. Baggerly

Jeffrey S. Morris

Proteomic expression patterns derived from mass spectrometry have been put forward as potential biomarkers for the early diagnosis of cancer and other diseases. This approach has generated much excitement and has led to a large number of new experiments and vast amounts of new data. The data, derived at great expense, can have very little value if careful attention is not paid to the experimental design and analysis. Using examples from surfaceenhanced laser desorption/ionisation time-of-flight (SELDI-TOF) and matrix-assisted laser desorption–ionisation/time-of-flight (MALDI-TOF) experiments, we describe several experimental design issues that can corrupt a dataset. Fortunately, the problems we identify can be …

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