Evidence map›Paper›PMID 23185041›Full record

ArticleNucleic acids research2013

ChemProt-2.0: visual navigation in a disease chemical biology database.

Sonny Kim Kjærulff, Louis Wich, Jens Kringelum, Ulrik P Jacobsen, Irene Kouskoumvekaki, Karine Audouze, Ole Lund, Søren Brunak, Tudor I Oprea, Olivier Taboureau

Abstract read
In one paragraph

Article in Nucleic acids research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

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

  1. Pooled it
  2. Large language models for bioinformatics.Quantitative biology (Beijing, China) · 2026
    Review
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. ChemProt-3.0: a global chemical biology diseases mapping.Database : the journal of biological databases and curation · 2016
    Article
  12. Article
  13. PhIN: A Protein Pharmacology Interaction Network Database.CPT: pharmacometrics & systems pharmacology · 2015
    Article
  14. Article
  15. Using VisANT to Analyze Networks.Current protocols in bioinformatics · 2014
    Article
  16. Article
  17. Article
  18. Article
  19. The CARLSBAD database: a confederated database of chemical bioactivities.Database : the journal of biological databases and curation · 2013
    Article
  20. Navigating traditional chinese medicine network pharmacology and computational tools.Evidence-based complementary and alternative medicine : eCAM · 2013
    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

10 authors.

Sonny Kim KjærulffCenter for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, 2800 Lyngby, Denmark.
Louis Wich
Jens Kringelum
Ulrik P Jacobsen
Irene Kouskoumvekaki
Karine Audouze
Ole Lund
Søren Brunak
Tudor I Oprea
Olivier Taboureau

Funding

Chemical Pattern Detection and Visualization in Biological NetworksR21GM095952 · NIGMS · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI OPREA, TUDOR I · 2011 to 2012
$415k
NIGMS NIH HHS R21 GM095952
6 · The paper itself

Abstract

ChemProt-2.0 (http://www.cbs.dtu.dk/services/ChemProt-2.0) is a public available compilation of multiple chemical-protein annotation resources integrated with diseases and clinical outcomes information. The database has been updated to >1.15 million compounds with 5.32 millions bioactivity measurements for 15 290 proteins. Each protein is linked to quality-scored human protein-protein interactions data based on more than half a million interactions, for studying diseases and biological outcomes (diseases, pathways and GO terms) through protein complexes. In ChemProt-2.0, therapeutic effects as well as adverse drug reactions have been integrated allowing for suggesting proteins associated to clinical outcomes. New chemical structure fingerprints were computed based on the similarity ensemble approach. Protein sequence similarity search was also integrated to evaluate the promiscuity of proteins, which can help in the prediction of off-target effects. Finally, the database was integrated into a visual interface that enables navigation of the pharmacological space for small molecules. Filtering options were included in order to facilitate and to guide dynamic search of specific queries.

Indexed as

Databases, ChemicalDiseaseComputer GraphicsDrug-Related Side Effects and Adverse ReactionsDrug TherapyHumansInternetPharmaceutical PreparationsProtein Interaction MappingProteinsSequence Analysis, ProteinUser-Computer InterfacePharmaceutical PreparationsProteins

Identifiers

PMID23185041
PMCPMC3531079

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.