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A logical framework for detecting anomalies in drug resistance algorithms

Published: 16 September 2009 Publication History

Abstract

Virology research is nowadays a discipline involving a broad number of researchers gathered in different institutes and cooperating on defined issues. An example of such an endeavor is the research tackling anti-HIV treatment problems [7] conducted within the Virolab project. The main objective of the ViroLab project is to develop a Virtual Laboratory for Infectious Diseases that facilitates medical knowledge discovery and decision support for HIV drug resistance. Large, high quality in-vitro and clinical patient databases which can be used to relate genotype to drug-susceptibility phenotype have become available. The core of the ViroLab Virtual Laboratory is a rule-based ranking system. More specifically, using a Grid-based service oriented architecture, Virolab vertically integrates the biomedical information from viruses (proteins and mutations), patients and literature (drug resistance experiments), resulting in a rule-based decision support system for drug ranking. This paper is a contribution to virologists, epidemiologists and clinicians in medical knowledge discovery and decision support. The final aim is reasoning on the properties of algorithm modeling the interaction among drugs and HIV virus and detecting its anomalies such as rules that can never be satisfied and subset of rules that are in contradiction.

References

[1]
Algorithm specification interface (asi). http://hivdb.stanford.edu/pages/asi/.
[2]
Hiv drug resistance database - stanford university. http://hivdb.stanford.edu/.
[3]
Retrogram. http://www.openclinical.org/aisp_retrogram.html.
[4]
The virolab project. http://www.virolab.org/.
[5]
Xml. http://www.w3.org/XML/.
[6]
P. M. A. Sloot. Virolab: from the molecule to the man. eStrategies Projects, (4):53--55, 2008.
[7]
P. M. A. Sloot, P. Coveney, G. Ertaylan, V. Muller, C. Boucher, and M. T. Bubak. Hiv decision support: From molecule to man. Phil. Trans. R. Soc. A, 367(1898), 2009.
[8]
P. M. A. Sloot, P. V. Coveney, M. T. Bubak, A. M. Vandamme, B. Ó Nualláin, D. van de Vijver, and C. A. B. Boucher. Virolab: A collaborative decision support system in viral disease treatment. Reviews in Antiviral Therapy, Virology Education, 3:4--7, 2008.
[9]
P. M. A. Sloot, A. Tirado-Ramos, I. Altintas, M. T. Bubak, and C. A. B. Boucher. From molecule to man: Decision support in individualized e-health. IEEE Computer, (Cover feature), 39(11):40--46, 2006.

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cover image ACM Conferences
IDEAS '09: Proceedings of the 2009 International Database Engineering & Applications Symposium
September 2009
347 pages
ISBN:9781605584027
DOI:10.1145/1620432
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 16 September 2009

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Author Tags

  1. anomalies in drug resistance algorithms
  2. bio-medical databases
  3. decision support system
  4. knowledge discovery
  5. logic programming
  6. rule-base system

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IDEAS '09
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  • ACM
  • Concordia University

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Overall Acceptance Rate 74 of 210 submissions, 35%

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