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Developing computational model-based diagnostics to analyse clinical chemistry data

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Author: Schalkwijk, D.B. van · Bochove, K. van · Ommen, B. van · Freidig, A.P. · Someren, E.P. van · Greef, J. van der · Graaf, A.A. de
Type:article
Date:2010
Institution: TNO Kwaliteit van Leven
Source:Briefings in Bioinformatics, 4, 11, 403-416
Identifier: 408486
doi: doi:10.1093/bib/bbp071
Article number: No.: bbp071
Keywords: Biology · Biomedical Research · Clinical chemistry · Clinical diagnostics · Computational modelling · Lipoprotein metabolism · Particle profiler · Probabilistic and deterministic modelling · Biomedical Innovation · Healthy Living · Life · MSB - Microbiology and Systems Biology MHR - Metabolic Health Research · EELS - Earth, Environmental and Life Sciences

Abstract

This article provides methodological and technical considerations to researchers starting to develop computational model-based diagnostics using clinical chemistry data.These models are of increasing importance, since novel metabolomics and proteomics measuring technologies are able to produce large amounts of data that are difficult to interpret at first sight, but have high diagnostic potential. Computational models aid interpretation and make the data accessible for clinical diagnosis. We discuss the issues that a modeller has to take into account during the design, construction and evaluation phases of model development.We use the example of Particle Profiler development, a model-based diagnostic tool for lipoprotein disorders, as a case study, to illustrate our considerations. The case study also offers techniques for efficient model formulation, model calculation, workflow structuring and quality control. © The Author 2010. Published by Oxford University Press.