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Paper Details

A Bayesian Null Interval Hypothesis Test Controls False Discovery Rates and Improves Sensitivity in Label-Free Quantitative Proteomics.
J Proteome Res
5
2020
Author NameAffiliation
Robert J MillikinUniversity of Wisconsin, 1101 University Avenue
Michael R ShortreedUniversity of Wisconsin, 1101 University Avenue
Mark ScalfUniversity of Wisconsin, 1101 University Avenue
Lloyd M SmithUniversity of Wisconsin, 1101 University Avenue
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Datasets

Dataset
Description
Source Link
ProteomeXchangeProteomics resources portalLink
ProteomeXchangeProteomics resources portalLink
ProteomeXchangeProteomics resources portalLink
ProteomeXchangeProteomics resources portalLink
ProteomeXchangeProteomics resources portalLink
ProteomeXchangeProteomics resources portalLink
ProteomeXchangeProteomics resources portalLink
ProteomeXchangeProteomics resources portalLink
ProteomeXchangeProteomics resources portalLink
ProteomeXchangeProteomics resources portalLink
ProteomeXchangeProteomics resources portalLink
ProteomeXchangeProteomics resources portalLink
ProteomeXchangeProteomics resources portalLink
ProteomeXchangeProteomics resources portalLink
ProteomeXchangeProteomics resources portalLink
Release 1.2