Evidence map›Paper›PMID 31665479›Full record

ArticleNucleic acids research2020

ProteomicsDB: a multi-omics and multi-organism resource for life science research.

Patroklos Samaras, Tobias Schmidt, Martin Frejno, Siegfried Gessulat, Maria Reinecke, Anna Jarzab, Jana Zecha, Julia Mergner, Piero Giansanti, Hans-Christian Ehrlich and 6 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 127 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
127citing 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

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

  1. Pooled it
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  4. Proteomic study for the prediction ofHistochemistry and cell biology · 2026
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67 more citing papers are in PubMed but not listed here.

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

16 authors.

Patroklos SamarasChair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany.
Tobias SchmidtChair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany.
Martin FrejnoChair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany.
Siegfried GessulatChair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany.
Maria ReineckeChair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany.
Anna JarzabChair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany.
Jana ZechaChair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany.
Julia MergnerChair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany.
Piero GiansantiChair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany.
Hans-Christian EhrlichInnovation Center Network, SAP SE, Potsdam, Germany.
Stephan AicheInnovation Center Network, SAP SE, Potsdam, Germany.
Johannes RankChair for Information Systems, Technical University of Munich (TUM), Garching, Germany.
Harald KieneggerChair for Information Systems, Technical University of Munich (TUM), Garching, Germany.
Helmut KrcmarChair for Information Systems, Technical University of Munich (TUM), Garching, Germany.
Bernhard KusterChair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany.
Mathias WilhelmChair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Bavaria, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

ProteomicsDB (https://www.ProteomicsDB.org) started as a protein-centric in-memory database for the exploration of large collections of quantitative mass spectrometry-based proteomics data. The data types and contents grew over time to include RNA-Seq expression data, drug-target interactions and cell line viability data. In this manuscript, we summarize new developments since the previous update that was published in Nucleic Acids Research in 2017. Over the past two years, we have enriched the data content by additional datasets and extended the platform to support protein turnover data. Another important new addition is that ProteomicsDB now supports the storage and visualization of data collected from other organisms, exemplified by Arabidopsis thaliana. Due to the generic design of ProteomicsDB, all analytical features available for the original human resource seamlessly transfer to other organisms. Furthermore, we introduce a new service in ProteomicsDB which allows users to upload their own expression datasets and analyze them alongside with data stored in ProteomicsDB. Initially, users will be able to make use of this feature in the interactive heat map functionality as well as the drug sensitivity prediction, but ultimately will be able to use all analytical features of ProteomicsDB in this way.

Indexed as

Biological Science DisciplinesDatabases, ProteinResearchComputational BiologyDrug DiscoveryProteomicsSoftwareUser-Computer InterfaceWeb Browser

Identifiers

PMID31665479
PMCPMC7145565

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.