Session: Annual Statistical Methodology Session: Statistics, Genomics and Public Health

4326.0: Tuesday, November 9, 2004: 4:30 PM-6:00 PM

Oral

Annual Statistical Methodology Session: Statistics, Genomics and Public Health

The term "genome" originated in the 1930's when it was used to denote the totality of genes on all chromosomes in the nucleus of a cell. However, DNA was not identified as the genetic material of all living organisms until 1944. Less than forty years later in 1981, the complete DNA sequence of an entire genome was first published. The circular DNA of a human mitochondrion is composed of a sequence of 16,159 letters in the genetic code, while the human genome has nearly 3 billion letters. Genomics is operationally defined as investigations into the structure and function of very large numbers of genes undertaken in a simultaneous fashion. The foundation of research efforts in structural and functional genomics is an enormous quantity of data, which is not easily examined or understood. Today, the acquisition of relational databases, as well as the development of efficient methods for searching and viewing these data, constitutes the field of "bioinformatics." More broadly, bioinformatics contains computational or algorithmic approaches to the production of information from large amounts of biological data, which might include prediction of protein structure, dynamic modeling of complex physiological systems or the statistical treatment of quantitative traits in populations in order to determine the genetic basis for these traits. The purpose of this session is to introduce individuals in the fields of biostatistics, environmental health and epidemiology to the role of quantitative methods in public health research.

Learning Objectives: At the end of this session the participant should be able to: 1. Define the terms human genome, genomics, functional genomics, structural genomics and bioinformatis 2. Decribe computational methods required for genomics research. 3. List statistical methods useful for understanding public health problems which can be addressed by genomics research. 4. Describe methods for identifying effects of heterogeneity on key disease outcomes and also suggest alternative approaches to risk prediction and clinical trial design.

Organizer(s):

Michael A. Newton, PhD

Facilitator(s):

Charity G. Moore, MSPH, PhD

4:30 PM

Introductory Remarks - Michael Newton, Ph.D., 2003 Spiegelman Award Recipient
Michael A. Newton, PhD

4:40 PM

Genetic heterogeneity, genomics and risk prediction