Baldur: Bayesian Hierarchical Modeling for Label-Free Proteomics with Gamma Regressing Mean-Variance Trends-Reference-Cited by-同舟云学术

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

Published:2023-12 Issue:12 Volume:22 Page:100658
ISSN:1535-9476
Container-title:Molecular & Cellular Proteomics
language:en
Short-container-title:Molecular & Cellular Proteomics

Author:

Berg Philip^ORCID,Popescu George^ORCID

Funder

National Science Foundation

Publisher

Elsevier BV

Subject

Molecular Biology,Biochemistry,Analytical Chemistry

Reference48 articles.

1. Tools for label-free peptide quantification;Nahnsen;Mol. Cell. Proteomics,2013

2. Stpeter: seamless label-free quantification with the trans-proteomic pipeline;Hoopmann;J. proteome Res.,2018

3. Benchmarking quantitative performance in label-free proteomics;Dowell;ACS Omega,2021

4. Proteome-wide evaluation of two common protein quantification methods;O’Connell;J. proteome Res.,2018

5. Superhirn–a novel tool for high resolution lc-ms-based peptide/protein profiling;Mueller;Proteomics,2007

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