Friday, May 25 at 3 pm Location: COOK 3118 A&B

Cliff Speigelman, Professor Department of Statistics, Texas A&M University University Title: Statistical considerations on the process of discovering and validating biomarker candidates using MS platforms (Joint with Lorenzo J. Vega Montoto and Asokan Mulayath Variyath)

Claims have been made that the application of supervised pattern recognition methodology can be used with MS proteomic data to achieve near perfect sensitivity and specificity for detecting early stage cancer. So far those claims have not been verified in part due to the use of less than optimal experimental design, but in the interim significant effort has been spent on proteomic biomarker discovery research (without significant positive results) largely using tandem MS platforms. Underpinning the proteomics studies are several key components including standardization of materials, bioinformatics, reagent development, MS improvements, and statistics. This presentation discusses the NCI CPTAC program generally and a related mouse studies project. Several areas where statistical design of experiment input is present will be discussed.

Created by Noelle I. Samia
Last Updated 05/08/2007