Classifiers based on molecular criteria such as gene expression signatures have been developed to distinguish Burkitt lymphoma and diffuse large B cell lymphoma, which help to explore the intermediate cases where traditional diagnosis is difficult. Transfer of these research classifiers into a clinical setting is challenging because there are competing classifiers in the literature based on different methodology and gene sets with no clear best choice; classifiers based on one expression measurement platform may not transfer effectively to another; and, classifiers developed using fresh frozen samples may not work effectively with the commonly used and more convenient formalin fixed paraffin-embedded samples used in routine diagnosis.
Pubmed ID: 26207141 RIS Download
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An integrated software for support vector classification, (C-SVC, nu-SVC), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM) from the laboratory of Chih-Chung Chang and Chih-Jen Lin. It supports multi-class classification.
View all literature mentionsSoftware R package of functions and classes for the analysis of oligonucleotide arrays manufactured by Affymetrix. Used to process probe level data and for exploratory oligonucleotide array analysis.
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