Expresso and Chips: Creating a Next Generation Microarray Experiment Management System

  • Authors:
  • Allan Sioson;Jonathan I. Watkinson;Cecilia Vasquez-Robinet;Margaret Ellis;Maulik Shukla;Deept Kumar;Naren Ramakrishnan;Lenwood S. Heath;Ruth Grene;Boris I. Chevone;Karen Kafadar;Layne T. Watson

  • Affiliations:
  • -;-;-;-;-;-;-;-;-;-;-;-

  • Venue:
  • IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
  • Year:
  • 2003

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Abstract

Expresso is an experiment management system that is designed to assist biologists in planning, executing, and interpreting microarray experiments. It serves as a unifying framework to study data-driven application composition systems, as envisaged under the NSF Next Generation Software (NGS) program. Physical and analytical stages of the microarray process are mirrored in Expresso with computational models from biophysics, molecular biology, biochemistry, robotics, image processing, statistics, and knowledge representation. These models are pushed deeper (earlier) into the design process to help avoid costly design errors and to provide, as needed, surrogate functions for the traditional stages of microarray experiments. In this paper, we describe ongoing work in the design of Expresso, with specific reference to application composition, application optimization, experiment protocol design, and closing the loop.'