Baldur: Bayesian Hierarchical Modeling for Label-Free Proteomics with Gamma Regressing Mean-Variance Trends.

Berg, Philip; Popescu, George

Berg, Philip; Popescu, George.

Afiliación

Berg P; Institute for Genomics, Biocomputing & Biotechnology, Mississippi State University, Mississippi State, Mississippi, USA; Department of Biochemistry, Molecular Biology, Entomology and Plant Pathology, Mississippi State University, Mississippi State, Mississippi, USA. Electronic address: pb1015@msstate.edu.
Popescu G; Institute for Genomics, Biocomputing & Biotechnology, Mississippi State University, Mississippi State, Mississippi, USA; Department of Biochemistry, Molecular Biology, Entomology and Plant Pathology, Mississippi State University, Mississippi State, Mississippi, USA. Electronic address: popescu@igbb.msstate.edu.

Mol Cell Proteomics ; 22(12): 100658, 2023 Dec.

Article en En | MEDLINE | ID: mdl-37806340

Asunto(s)

Proteínas; Proteómica; Proteómica/métodos; Teorema de Bayes; Proteínas/química; Péptidos/metabolismo; Espectrometría de Masas/métodos

Palabras clave

Bayesian hierarchical model; data-independent acquisition; empirical Bayes; label-free quantification; latent gamma mixture regression; mean-variance trends; proteomics; uncertainty modeling

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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Proteínas / Proteómica Tipo de estudio: Prognostic_studies Idioma: En Revista: Mol Cell Proteomics Asunto de la revista: BIOLOGIA MOLECULAR / BIOQUIMICA Año: 2023 Tipo del documento: Article

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