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Recent advances in liquid chromatography-mass spectrometry (LC-MS) technology have led to newer approaches for measuring changes in peptide/protein abundances. Label-free LC-MS methods have been used for extraction of quantitative information and for detection of differentially abundant peptides/proteins. However, difference detection by analysis of data derived from label-free LC-MS methods requires...
Pancreatic cancer (PC) is the fourth leading cause of cancer death in the United States, with 4% survival 5 years after diagnosis. Patients with pancreatic cancer are usually diagnosed at late stages, when the disease is incurable. Sensitive and more specific biomarkers are thus critical for supporting new prevention, diagnostic or therapeutic strategies. Here, we report mass spectrometry-based metabolomic...
Mass spectrometry-based metabolomics is getting mature and playing an ever important role in the systematic understanding of biological process in conjunction with other members of “-omics” family. However, the identification of metabolites in untargeted metabolomics profiling remains a challenge. In this paper, we propose a support vector machine (SVM)-based spectral matching algorithm to combine...
In this paper, we introduce a novel feature selection method that combines ant colony optimization (ACO) with support vector machine (SVM) to identify candidate biomarkers from mass spectral serum profiles. In addition, we present an innovative rule extraction algorithm that uses ACO to select accurate if-then rules for the classification of mass spectra. We applied the proposed feature selection...
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