Multi-science decision support for HIV drug resistance treatment

Peter Sloot; Peter Coveney; Marian T. Bubak; Anne Mieke Vandamme; Breanndán Ó Nualláin; David Van De Vijver; Charles Boucher

Multi-science decision support for HIV drug resistance treatment

Peter Sloot^*, Peter Coveney, Marian T. Bubak, Anne Mieke Vandamme, Breanndán Ó Nualláin, David Van De Vijver, Charles Boucher

^*Corresponding author for this work

Virology

Research output: Contribution to journal › Conference article › Academic › peer-review

7 Citations (Scopus)

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Abstract

The complete cascade from genome, proteome, metabolome, and physiome, to health forms multiscale, multiscience systems and crosses many orders of magnitude in temporal and spatial scales. The interactions between these systems create exquisite multitiered networks, with each component in nonlinear contact with many interaction partners. Understanding, quantifying, and handling this complexity is one of the biggest scientific challenges of our time. In this paper we argue that computer science in general, and Grid computing in particular, provide the language needed to study and understand these systems, and discuss a case study in decision support for HIV drug resistance treatment within the European ViroLab project.

Original language	English
Pages (from-to)	188-198
Number of pages	11
Journal	Studies in Health Technology and Informatics
Publication status	Published - 2008
Event	6th Annual HealthGrid Conference - Global HealthGrid: E-Science Meets Biomedical Informatics, HealthGrid 2008 - Chicago, IL, United States Duration: 2 Jun 2008 → 4 Jun 2008

Bibliographical note

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Sloot2008cFinal published version, 299 KBLicence: CC BY

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Cite this

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title = "Multi-science decision support for HIV drug resistance treatment",

abstract = "The complete cascade from genome, proteome, metabolome, and physiome, to health forms multiscale, multiscience systems and crosses many orders of magnitude in temporal and spatial scales. The interactions between these systems create exquisite multitiered networks, with each component in nonlinear contact with many interaction partners. Understanding, quantifying, and handling this complexity is one of the biggest scientific challenges of our time. In this paper we argue that computer science in general, and Grid computing in particular, provide the language needed to study and understand these systems, and discuss a case study in decision support for HIV drug resistance treatment within the European ViroLab project.",

author = "Peter Sloot and Peter Coveney and Bubak, {Marian T.} and Vandamme, {Anne Mieke} and Nuall{\'a}in, {Breannd{\'a}n {\'O}} and {Van De Vijver}, David and Charles Boucher",

note = "Copyright {\textcopyright} 2007 The Authors; 6th Annual HealthGrid Conference - Global HealthGrid: E-Science Meets Biomedical Informatics, HealthGrid 2008 ; Conference date: 02-06-2008 Through 04-06-2008",

year = "2008",

language = "English",

pages = "188--198",

journal = "Studies in Health Technology and Informatics",

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T1 - Multi-science decision support for HIV drug resistance treatment

AU - Sloot, Peter

AU - Coveney, Peter

AU - Bubak, Marian T.

AU - Vandamme, Anne Mieke

AU - Nualláin, Breanndán Ó

AU - Van De Vijver, David

AU - Boucher, Charles

PY - 2008

Y1 - 2008

N2 - The complete cascade from genome, proteome, metabolome, and physiome, to health forms multiscale, multiscience systems and crosses many orders of magnitude in temporal and spatial scales. The interactions between these systems create exquisite multitiered networks, with each component in nonlinear contact with many interaction partners. Understanding, quantifying, and handling this complexity is one of the biggest scientific challenges of our time. In this paper we argue that computer science in general, and Grid computing in particular, provide the language needed to study and understand these systems, and discuss a case study in decision support for HIV drug resistance treatment within the European ViroLab project.

AB - The complete cascade from genome, proteome, metabolome, and physiome, to health forms multiscale, multiscience systems and crosses many orders of magnitude in temporal and spatial scales. The interactions between these systems create exquisite multitiered networks, with each component in nonlinear contact with many interaction partners. Understanding, quantifying, and handling this complexity is one of the biggest scientific challenges of our time. In this paper we argue that computer science in general, and Grid computing in particular, provide the language needed to study and understand these systems, and discuss a case study in decision support for HIV drug resistance treatment within the European ViroLab project.

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M3 - Conference article

C2 - 18560121

AN - SCOPUS:53249099016

SN - 0926-9630

SP - 188

EP - 198

JO - Studies in Health Technology and Informatics

JF - Studies in Health Technology and Informatics

T2 - 6th Annual HealthGrid Conference - Global HealthGrid: E-Science Meets Biomedical Informatics, HealthGrid 2008

Y2 - 2 June 2008 through 4 June 2008

ER -

Multi-science decision support for HIV drug resistance treatment

Abstract

Bibliographical note

UN SDGs

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