Peptide-level Robust Ridge Regression Improves Estimation, Sensitivity, and Specificity in Data-dependent Quantitative Label-free Shotgun Proteomics.

Goeminne, Ludger J E; Gevaert, Kris; Clement, Lieven

Goeminne, Ludger J E; Gevaert, Kris; Clement, Lieven.

Afiliação

Goeminne LJ; From the Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Belgium; §VIB Medical Biotechnology Center, Ghent University, Belgium; ¶Department of Biochemistry, Ghent University, Belgium.
Gevaert K; §VIB Medical Biotechnology Center, Ghent University, Belgium; ¶Department of Biochemistry, Ghent University, Belgium.
Clement L; From the Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Belgium; ludger.goeminne@UGent.be kris.gevaert@UGent.be lieven.clement@UGent.be.

Mol Cell Proteomics ; 15(2): 657-68, 2016 Feb.

Article em En | MEDLINE | ID: mdl-26566788

Assuntos

Peptídeos/genética; Proteoma/genética; Proteômica/métodos; Teorema de Bayes; Modelos Lineares; Espectrometria de Massas; Proteômica/estatística & dados numéricos

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Peptídeos / Proteoma / Proteômica Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Ano de publicação: 2016 Tipo de documento: Article

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