Work

Bayesian Proteoform Modeling Improves Protein Quantification of Global Proteomic Measurements

Year: 2014

Type: article

Source: Molecular & Cellular Proteomics

DOI: 10.1074/mcp.o113.030932

Authors: B.-J. M. Webb-Robertson, M. M. Matzke, S. Datta, S. H. Payne, J. Kang, L. M. Bramer, C. D. Nicora, A. K. Shukla, T. O. Metz, K. D. Rodland, R. D. Smith, M. F. Tardiff, J. E. McDermott, J. G. Pounds, K. M. Waters

Institutions: Pacific Northwest National Laboratory, University of Louisville

Language: English

Topic: Advanced Proteomics Techniques and Applications

Subfield: Spectroscopy

Field: Chemistry

Domain: Physical Sciences

Open Access status: closed

Funder: National Cancer Institute

Award: Identification of Proteins from Mass Spectrometry Data: A Statistical Approach

OpenAlex ID: W4249064854

FWCI:

Cites:

Cited by: 1

Related to: 10