SAC2003 - Tracks

Abstract
The new era of high throughput molecular instrumentation is generating important biomedical data at a rapidly increasing rate. The analysis and interpretation of this data must transcend traditional approaches to statistical hypothesis testing, toward more general computational support for biomedical discovery. In this talk I will argue that knowledge-based approaches, ranging from graphical statistical models with informative priors, to rule-based inference, to knowledge-based information extraction from natural language are the best way to meet this key challenge of the 21st century.

Speaker's Bio
Dr. Lawrence Hunter is the Director of the Center for Computational Pharmacology at the University of Colorado School of Medicine, and an Associate Professor in the departments of Pharmacology, Computer Science, and Preventative Medicine and Biometrics. Is is also a founder and director of Molecular Mining Corporation. He received his Ph.D. in computer science from Yale University in 1989, and then spent more than 10 years at the National Institutes of Health, ending as the Chief of the Molecular Statistics and Bioinformatics Section at the National Cancer Institute. He inaugurated two of the most important academic Bioinformatics conferences, ISMB and PSB, and was the founding President of the International Society for Computational Biology. Dr. Hunter's research interests span a wide range of areas, from cognitive science to rational drug design. His primary focus recently has been the application of machine learning techniques to data generated by high throughput molecular biology.

The Software Engineering of Applications - Deploying Mission Critical Applications in an Era of Pervasive Computing
By Mr. Richard Simonian
Vice President of Engineering
Harris Corporation in Melbourne, Florida, USA

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Tuesday March 11, 2003 - Keynote Address
8:30AM - 10:00AM

Abstract
Given that software now pervades every aspect of our society, and "all science is computer science," we need to review the role and definition of a software engineer. The transition of research into mission critical applications is seldom smooth in any engineering discipline, and even more difficult with distributed software. This is partly due to the lack of agreement on what a software engineering profession is (especially between academia and industry), and the failure to apply even basic software processes early in the research lifecycle. In this talk I discuss how fundamental system architecting principles are helpful to drive meaningful research and development, how to apply processes for development both "in the small" and "in the large", and approaches to bridge the gap between researchers and mission success.

Speaker's Bio
Mr. RICHARD SIMONIAN is Vice President of Engineering for the Government Communication Systems Division of Harris Corporation in Melbourne, Florida. Harris is a $2B company delivering assured communication products and services to customers around the world. GCSD is an SEI SW CMM Level 4 organization. All 600 Software Engineers for GCSD report to Mr. Simonian, as well as the Support System Engineers and Systems Engineers. These engineers primarily provide U.S. Government agencies with large, complex communication and information processing systems for various missions, such as assured ground communication systems, wide-band high speed communications, voice switching and telecommunication systems, intelligence systems, weather data management and processing, satellite image processing, air to ground communication, tactical communications, large scale archival and dissemination systems, and information assurance. Mr. Simonian has extensive background in software project management and software processes, application of modern software methodologies, research and development planning, and management of information technology advances. He has been with Harris Corporation in various engineering roles since 1985. Mr. Simonian has a BS in Computer Science from the College of Engineering at Ohio State University, and an MS in Computer Science from the College of Engineering at the University of Florida. He is a long time member of the ACM, Chair for the University of Florida Dean's Advisory Board, and Vice-Chair for the University of Central Florida Industry Advisory Board.

Computational Biology: An Industrial Perspective
By Dr. Lee Weng
Director of Applied Research
Rosetta Biosoftware

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Monday March 10, 2003 - Luncheon Speaker
Noon - 1:30PM

Abstract
Large-scale data acquisition technologies, such as gene expression microarrays, have revolutionized molecular biology research and drug discovery process. The increasing volume and complexity of data have created demands for more powerful analysis and data management tools. These new tools are developed with the primary goals of creating higher statistical analysis power and discovering more valuable information in the data. I will use the Rosetta Resolver system for gene expression data analysis as an example to discuss the challenges we are facing in providing these tools for the revolution in computational biology. This system serves as a centerpiece in an enterprise environment to process and manage data from hundreds and thousands of high-density microarrays routinely. Although the total amount of data is enormous in microarray studies, the number of replications is usually too small to make reliable statistical inferences based on conventional statistical methods. The error model technology in the Rosetta Resolver system provides a major breakthrough in handling microarray data with low replications. It offers significantly higher power in statistical analysis, such as ANOVA, than the conventional textbook method. To explore the biologically important information hidden in the vast amount microarray data, the system provides unsupervised and supervised data mining capabilities to help biologists gain new knowledge from the data. One example is demonstrated in the recently published results where a supervised learning tool is used in breast cancer studies to classify and predict patients' prognoses based on their gene expression profiles. As a part of the emerging bioinformatics industry, we will provide more software products that are specifically designed to meet more demanding regulatory environments and higher expectations in pharmaceutical and biotechnology research.

Speaker's Bio
Dr. Lee Weng is the Director of Applied Research at Rosetta Biosoftware, a division of Rosetta Inpharmatics LLC. Rosetta Biosoftware develops bioinformatics software products for pharmaceutical/biotech companies and academic institutions. He leads the bioinformatics research and development projects in Rosetta Biosoftware to develop statistical error models and analysis tools for gene and protein expressions. Many innovative algorithms he and others developed overcome limitations in traditional statistics. Supervised and unsupervised computer learning methods in Rosetta software
products also help life scientists to understand molecular biology and to discover new therapeutic targets. He received his Ph.D. in Biomedical Engineering from Drexel University in 1990.