Cancer Genome Analyses

Chad J. Creighton,

Ph.D., Department of Medicine,

Baylor College of Medicine, Houston, TX

Abstract

Bioinformatics is an interdisciplinary field that utilizes computer science and statistics to analyze large-scale biomolecular datasets. These datasets can involve various “omics” platforms that profile the cell at different levels of molecular complexity, including RNA expression, protein expression, DNA methylation, somatic mutation, or DNA copy number. The vast amount of molecular profiling data from human tumor samples and bench experiments available in the public domain represents a tremendous resource. For any major cancer type defined by tissue of origin, molecular profiling data can identify molecular subtypes, predict patient outcome, identify markers of therapeutic response, determine the functional consequences of somatic mutation, and elucidate the biology of metastatic and advanced cancers. In addition, pan-cancer molecular studies can facilitate a better understanding of the molecular underpinnings and pathways of cancer beyond tissue-oriented domains, with therapeutic implications. This seminar will provide a broad overview of molecular profiling studies in cancer and the types of findings that can be made using these data.

Biography

Chad J. Creighton, PhD, is a full Professor in the Department of Medicine and the Dan L. Duncan Comprehensive Cancer Center at Baylor College of Medicine. He obtained his Ph.D. degree in Bioinformatics in 2006 from the University of Michigan in Ann Arbor. Then, he joined Baylor College of Medicine, receiving tenure in 2013. His research mainly focuses on bioinformatics analysis and integrating molecular profiling data representing various -omics levels, including protein expression, mRNA and microRNA expression, DNA methylation, somatic mutation, structural variation, and DNA copy number.

Models for Pressure Rise and Flame Speed for the Combustion of Aluminum in Closed, Spherical Vessels

Henry Foust, Ph.D.,

Department of Computer Science and Engineering Technology,

University of Houston, Downtown

Abstract

In this presentation, models will be developed for pressure rise and flame speed associated with the combustion of aluminum particles in a 20-liter, closed spherical vessel. Typically, the pressure rise has been modeled assuming the combustion fuel is a gas and this results in an erroneous pressure rise curve; this work will provide a model that fits the experimental data well. The pressure rise model comes from an understanding of the kinetics and these same kinetics form the basis to the flame speed model, which is validated against experimental results. The presentation will go on to explore the effects of particle shape on the time to maximum pressure (TMP) and how TMP affects global combustion properties such as flame speed, K(st), and (dP/dt)max.