Evidence map›Paper›PMID 33711481›Full record

ArticleMolecular & cellular proteomics : MCP2021

Data Management of Sensitive Human Proteomics Data: Current Practices, Recommendations, and Perspectives for the Future.

Nuno Bandeira, Eric W Deutsch, Oliver Kohlbacher, Lennart Martens, Juan Antonio Vizcaíno

Abstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Digital Twin Technology In Radiology.Journal of imaging informatics in medicine · 2026
    Review
  5. Article
  6. Review
  7. Article
  8. Article
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  10. Review
  11. Article
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  15. Article
  16. To share is to be a scientist.Nature methods · 2023
    Article
  17. Article
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Nuno BandeiraCenter for Computational Mass Spectrometry, University of California, San Diego (UCSD), La Jolla, California, USA; Department Computer Science and Engineering, University of California, San Diego (UCSD), La Jolla, California, USA; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego (UCSD), La Jolla, California, USA.
Eric W DeutschInstitute for Systems Biology, Seattle, Washington, USA.
Oliver KohlbacherInstitute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany; Quantitative Biology Center, University of Tübingen, Tübingen, Germany; Biomolecular Interactions, Max Planck Institute for Developmental Biology, Tübingen, Germany; Institute for Translational Bioinformatics, University Hospital Tübingen, Tübingen, Germany.
Lennart MartensVIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium.
Juan Antonio VizcaínoEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom. Electronic address: juan@ebi.ac.uk.

Funding

Systems BiologyU19AG023122 · NIA · TRANSLATIONAL GENOMICS RESEARCH INST · PI JODI A LAPIDUS · 2004 to 2026
$102.6M
TrainingP41GM103484 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PEVZNER, PAVEL A · 2012 to 2018
$8.7M
Shortening the development cycle time of Trans Proteomic Pipeline tools with high performance computingR01GM087221 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI DEUTSCH, ERIC, MORITZ, ROBERT L · 2010 to 2021
$6.0M
MassIVE.quant: a curated and scalable community resource for quantitative proteomicsR01LM013115 · NLM · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BANDEIRA, NUNO · 2019 to 2022
$1.3M
Advancing data and metadata standards for proteomics mass spectraR24GM127667 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI DEUTSCH, ERIC · 2017 to 2019
$1.2M
Biotechnology and Biological Sciences Research Council BB/P024599/1NIA NIH HHS U19 AG023122NIGMS NIH HHS P41 GM103484NIGMS NIH HHS R01 GM087221NIGMS NIH HHS R24 GM127667NLM NIH HHS R01 LM013115Wellcome TrustWellcome Trust 208391/Z/17/Z
6 · The paper itself

Abstract

Today it is the norm that all relevant proteomics data that support the conclusions in scientific publications are made available in public proteomics data repositories. However, given the increase in the number of clinical proteomics studies, an important emerging topic is the management and dissemination of clinical, and thus potentially sensitive, human proteomics data. Both in the United States and in the European Union, there are legal frameworks protecting the privacy of individuals. Implementing privacy standards for publicly released research data in genomics and transcriptomics has led to processes to control who may access the data, so-called "controlled access" data. In parallel with the technological developments in the field, it is clear that the privacy risks of sharing proteomics data need to be properly assessed and managed. In our view, the proteomics community must be proactive in addressing these issues. Yet a careful balance must be kept. On the one hand, neglecting to address the potential of identifiability in human proteomics data could lead to reputational damage of the field, while on the other hand, erecting barriers to open access to clinical proteomics data will inevitably reduce reuse of proteomics data and could substantially delay critical discoveries in biomedical research. In order to balance these apparently conflicting requirements for data privacy and efficient use and reuse of research efforts through the sharing of clinical proteomics data, development efforts will be needed at different levels including bioinformatics infrastructure, policymaking, and mechanisms of oversight.

Indexed as

Data ManagementProteomicsConfidentialityHumansInformation Disseminationcontrolled access datadatabasesethicsmass spectrometrypolicyproteomics

Identifiers

PMID33711481
PMCPMC8056256

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.