Computational models for analyzing lipoprotein profiles
article
At present, several measurement technologies are available for generating highly detailed concentration-size profiles of lipoproteins, offering increased diagnostic potential. Computational models are useful in aiding the interpretation of these complex datasets and making the data more accessible for clinical diagnosis. They do so by calculating hitherto inaccessible biological parameters that underlie the profile. Their application results in new markers that have been demonstrated to improve diagnosis of dyslipidemias compared with the classical plasma markers, LDL-C, HDL-C and total triglycerides. Whether the new diagnostic markers contribute to cardiovascular and diabetes risk prediction is currently under investigation. © 2011 Future Medicine Ltd.
Topics
TNO Identifier
427547
ISSN
17460875
Source
Clinical Lipidology, 6(1), pp. 25-33.
Pages
25-33
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