Evidence map›Paper›PMID 20935044›Full record

ArticleNucleic acids research2011

ChemProt: a disease chemical biology database.

Olivier Taboureau, Sonny Kim Nielsen, Karine Audouze, Nils Weinhold, Daniel Edsgärd, Francisco S Roque, Irene Kouskoumvekaki, Alina Bora, Ramona Curpan, Thomas Skøt Jensen and 2 more

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 1 pooled it
10.7field-weighted citation impact, top 1% of its field
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

42 citing papers in PubMed, 1 synthesis or guideline pooled it, 106 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Large language models for bioinformatics.Quantitative biology (Beijing, China) · 2026
    Review
  4. Article
  5. Scaling Biomedical Text-Mining: Transformers, GenAI, and Drug Discovery.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Revisiting Relation Extraction in the era of Large Language Models.Proceedings of the conference. Association for Computational Linguistics. Meeting · 2023
    Article
  13. Neighborhood-Regularized Self-Training for Learning with Few Labels.Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence · 2023
    Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Review
  20. Review
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

12 authors at 2 institutions in 3 countries.

Olivier TaboureauDepartment of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby, DK-2800 Denmark. otab@cbs.dtu.dk
Sonny Kim Nielsen
Karine Audouze
Nils Weinhold
Daniel Edsgärd
Francisco S Roque
Irene Kouskoumvekaki
Alina Bora
Ramona Curpan
Thomas Skøt Jensen
Søren Brunak
Tudor I Oprea
University of New Mexico · USTechnical University of Denmark · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Systems pharmacology is an emergent area that studies drug action across multiple scales of complexity, from molecular and cellular to tissue and organism levels. There is a critical need to develop network-based approaches to integrate the growing body of chemical biology knowledge with network biology. Here, we report ChemProt, a disease chemical biology database, which is based on a compilation of multiple chemical-protein annotation resources, as well as disease-associated protein-protein interactions (PPIs). We assembled more than 700,000 unique chemicals with biological annotation for 30,578 proteins. We gathered over 2-million chemical-protein interactions, which were integrated in a quality scored human PPI network of 428,429 interactions. The PPI network layer allows for studying disease and tissue specificity through each protein complex. ChemProt can assist in the in silico evaluation of environmental chemicals, natural products and approved drugs, as well as the selection of new compounds based on their activity profile against most known biological targets, including those related to adverse drug events. Results from the disease chemical biology database associate citalopram, an antidepressant, with osteogenesis imperfect and leukemia and bisphenol A, an endocrine disruptor, with certain types of cancer, respectively. The server can be accessed at http://www.cbs.dtu.dk/services/ChemProt/.

Indexed as

Databases, FactualDrug DiscoveryDiseaseGenesHumansPharmaceutical PreparationsProtein Interaction MappingProteinsPharmaceutical PreparationsProteins

Identifiers

PMID20935044
PMCPMC3013776
OpenAlexW2132267839

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.