Abstract
We present a method for prognostics biomarker mining based on a genetic algorithm with a novel fitness function and a bagging-like model averaging scheme. We demonstrate it on publicly available data sets of gene expressions in colon cancer tissue specimens and assess the relevance of the discovered biomarkers by means of a qualitative analysis. Furthermore, we test performance of the method on the cancer recurrence prediction task using two independent external validation sets. The obtained results correspond to the top published performances of gene signatures developed specially for the colon cancer case. © 2012 Springer-Verlag.
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Popovic, D., Sifrim, A., Pavlopoulos, G. A., Moreau, Y., & De Moor, B. (2012). A simple genetic algorithm for biomarker mining. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7632 LNBI, pp. 222–232). https://doi.org/10.1007/978-3-642-34123-6_20
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