Rather than focusing on individual or pairs of genetic variations in tumors, the M. D. Anderson analysis center will study multi-gene pathways and combinations of pathways, a systems biology approach that addresses the complexity of cancer growth and survival.
Weinstein's group is developing a bioinformatic pipeline to analyze TCGA data and translate findings to the clinic. "We will use several nuggets of innovation to develop applications that will usefully address the questions that biologists and clinicians have at the end of the day," Weinstein said.
A major strength of the project is M. D. Anderson's leading expertise in translational and clinical research, Weinstein said. That expertise will keep bioinformatics development connected to important questions that must be addressed for each tumor type and for different types of molecular information. Additionally, M. D. Anderson is by far the largest contributor of tumor tissue samples to TCGA. That will be particularly important in the study of less common cancers.
The team will tap M. D. Anderson's leadership in the use of Bayesian statistical analysis, an efficient and informative approach to data analysis and clinical trial design, as developed under Donald Berry, Ph.D., Professor and Head of the Division of Quantitative Sciences.
Weinstein and colleagues will apply a number of advanced computational tools and concepts based on pathway analyses, artificial intelligence-based prediction methods, and the clustered heat map representations of genomic data that Weinstein introduced in the early 1990s.
Professor of Bioinformatics and Computational Biology Jonas Almeda, Ph.D., is a leading expert in semantic web, a flexible database infrastructure that's easily expandable to accommodate new types of searches. Searching a standard relational database requires loading the data and then sea
|Contact: Scott Merville|
University of Texas M. D. Anderson Cancer Center