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A generalizable method for false-discovery rate estimation in mass spectrometry-based lipidomics

bioRxiv (Cold Spring Harbor Laboratory)(2020)10.1101/2020.02.18.946483Source: DataRank Database

A generalizable method for false-discovery rate estimation in mass spectrometry-based lipidomics is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2020). On theSindex it has a DataRank of 0. It has been cited 1 time.

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (3 grants)OA: greenTopics (20)IDs (PubMed, OpenAlex)

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Authors (5)

Jennifer Kyle ORCID,Joon‐Yong Lee ORCID,Thomas Metz ORCID,Samuel H. Payne ORCID,Grant M. Fujimoto ORCID

Live enrichment

PubMed:23304386 OpenAlex:https://openalex.org/W3006804832

National Institutes of Health

Grant: 5U01HL122703-05

Center for Lung Development Imaging and Omics

Fundação para a Ciência e a Tecnologia, I.P.

Grant: PTDC/CCI-INF/6762/2020

MS3: New foundations for micro-services and serverless systems

National Institutes of Health

Grant: 5U19AI106772-03

Systems Biology Analysis of Influenza A Virus and Ebola Virus

greenLicense: cc-by

repositoryhttps://www.biorxiv.org/content/biorxiv/early/2020/02/19/2020.02.18.946483.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2020.02.18.946483

repositoryhttps://doi.org/10.1101/2020.02.18.946483

https://dx.doi.org/10.1101/2020.02.18.946483

Fields of Study

Metabolomics and Mass Spectrometry StudiesAdvanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and Applications0301 basic medicine03 medical and health sciences

Keywords

LipidomicsFalse discovery rateContext (archaeology)Identification (biology)False positive rateComputer scienceMultiple comparisons problemComputational biologyData miningBioinformaticsArtificial intelligenceStatisticsChemistryBiologyMathematics