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. 2003 Sep;3(9):1678-9.
doi: 10.1002/pmic.200300521.

Decision tree classification of proteins identified by mass spectrometry of blood serum samples from people with and without lung cancer

Mia K Markey  1 , Georgia D Tourassi, Carey E Floyd Jr
Affiliations

Decision tree classification of proteins identified by mass spectrometry of blood serum samples from people with and without lung cancer

Mia K Markey et al. Proteomics. 2003 Sep.

Abstract

A classification and regression tree (CART) model was trained to classify 41 clinical specimens as disease/nondisease based on 26 variables computed from the mass-to-charge ratio (m/z) and peak heights of proteins identified by mass spectroscopy. The CART model built on all of the specimens (no cross-validation) had an error rate of 4/41 = 10%. The CART model suggests that mass spectra peaks in the 8000-10,000, 20,000-30,000, 45,000-60, 000, and >125,000 m/z ranges may be valuable in distinguishing between the disease/nondisease specimens. The area under the receiver operating characteristics curve was 0.80 +/- 0.07 for leave-one-out cross-validation.

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