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Two Challenges in Genomics That Can Benefit from Petascale Platforms

  • Catherine Putonti
  • Meizhuo Zhang
  • Lennart Johnsson
  • Yuriy Fofanov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4375)

Abstract

Supercomputing and new sequencing techniques have dramatically increased the number of genomic sequences now publicly available. The rate in which new data is becoming available, however, far exceeds the rate in which one can perform analysis. Examining the wealth of information contained within genomic sequences presents numerous additional computational challenges necessitating high-performance machines. While there are many challenges in genomics that can greatly benefit from the development of more expedient machines, herein we will focus on just two projects which have direct clinical applications.

Keywords

Human Leukocyte Antigen Preimplantation Genetic Diagnosis Candidate Probe Human Leukocyte Antigen Region International HapMap Consortium 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Catherine Putonti
    • 1
    • 2
  • Meizhuo Zhang
    • 1
  • Lennart Johnsson
    • 1
  • Yuriy Fofanov
    • 1
    • 2
  1. 1.University of Houston, Department of Computer Science, 218 Philip G. Hoffman Hall, Houston, Texas 77204-3058USA
  2. 2.University of Houston, Department of Biology and Biochemistry, Houston, Texas 77204-5001USA

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