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Computational Approaches for Translational Clinical Research in Disease Progression
  1. Mary F. McGuire, MS*,
  2. Madurai Sriram Iyengar, PhD*,
  3. David W. Mercer, MD
  1. From the *School of Biomedical Informatics, University of Texas Health Science Center at Houston, TX; and †Department of Surgery, University of Nebraska Medical Center, Omaha, NE.
  1. Received September 28, 2010, and in revised form May 3, 2011.
  2. Accepted for publication May 13, 2011.
  3. Reprints: Mary F. McGuire, MS, School of Biomedical Informatics, University of Texas Health Science Center at Houston, 7000 Fannin, #600, Houston, TX 77030. E-mail: mary.f.mcguire{at}uth.tmc.edu.
  4. This work was supported by the National Institutes of Health (T15-LM07093-16 to M.F.M. and GM-38529, GM-08792, CReFF UCRC no. M01RR002558 to D.W.M.).
  5. The authors have no conflicts of interest to declare.
  6. Supplemental digital content is available for this article. Direct URL citation appears in the printed text and is provided in the HTML and PDF versions of this article on the journal's Web site (www.jinvestigativemed.com).

Abstract

Today, there is an ever-increasing amount of biological and clinical data available that could be used to enhance a systems-based understanding of disease progression through innovative computational analysis. In this article, we review a selection of published research regarding computational methods, primarily from systems biology, which support translational research from the molecular level to the bedside, with a focus on applications in trauma and critical care. Trauma is the leading cause of mortality in Americans younger than 45 years, and its rapid progression offers both opportunities and challenges for computational analysis of trends in molecular patterns associated with outcomes and therapeutic interventions.

This review presents methods and domain-specific examples that may inspire the development of new algorithms and computational methods that use both molecular and clinical data for diagnosis, prognosis, and therapy in disease progression.

Key Words
  • systems biology
  • computational methods
  • trauma
  • biomedical informatics

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