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Follicular lymphoma (FL) is the second most common non-Hodgkins lymphoma in the United States. While the current diagnosis depends heavily on the review of H&E-stained tissues, additional sources of information such as IHC are occasionally needed. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) can be used to generate protein profiles from localized tissue regions, thus...
Mass spectrometry technique is a revolutionary tool for diagnosing early stage cancer by analyzing protein mass spectra, and for detecting biomarkers. But because of the high dimensionality of the data, feature selection is a necessary procedure before classification and analysis. In this paper we present a genetic algorithm for feature selection for prostate protein mass spectrometry data. An elitism...
We present a computational framework to analyze MALDI-TOF mass spectrometry data for quantitative comparison of peptides and glycans in serum. In particular, we introduce an algorithm that detects peaks that are differentially abundant in a subgroup of patients. The method is applied to identify candidate biomarkers in serum samples of 203 participants from Egypt; 73 hepatocellular carcinoma (HCC)...
Protein mass spectra pattern recognition is a new forum in which many machine learning algorithms have been conducted to enhance the chance of early cancer diagnosis. The high-dimensionality-small-sample (HDSS) problem of cancer proteomic datasets still requires more sophisticated approaches to improve the classification accuracy. In this study we present a simple ensemble strategy based on measuring...
High-throughput mass spectrometry and statistical analysis methodologies are promising technologies to aid the medical diagnostics field by detecting the cancer-related proteomic markers. We propose statistical methods to cull the potential markers by ranking them in relations to their power of separability distinguishing cancerous patients from normal persons or among different cancer stages. To...
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