Feature Construction Can Improve Diagnostic Criteria for High-Dimensional Metabolic Data in Newborn Screening for Medium-Chain Acyl-CoA Dehydrogenase Deficiency | Zendy

S. Ho | Zendy; Zoltán Lukács | Zendy; Georg F. Hoffmann | Zendy; Martin Lindner | Zendy; Thomas C. Wetter | Zendy

Open Access

Feature Construction Can Improve Diagnostic Criteria for High-Dimensional Metabolic Data in Newborn Screening for Medium-Chain Acyl-CoA Dehydrogenase Deficiency

Author(s) -

S. Ho,

Zoltán Lukács,

Georg F. Hoffmann,

Martin Lindner,

Thomas C. Wetter

Publication year - 2007

Publication title -

clinical chemistry

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.705

H-Index - 218

eISSN - 1530-8561

pISSN - 0009-9147

DOI - 10.1373/clinchem.2006.081802

Subject(s) - analyte , newborn screening , computational biology , feature (linguistics) , computer science , chemistry , biochemistry , biology , chromatography , philosophy , linguistics

In newborn screening with tandem mass spectrometry, multiple intermediary metabolites are quantified in a single analytical run for the diagnosis of fatty-acid oxidation disorders, organic acidurias, and aminoacidurias. Published diagnostic criteria for these disorders normally incorporate a primary metabolic marker combined with secondary markers, often analyte ratios, for which the markers have been chosen to reflect metabolic pathway deviations.

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