Evidence map›Paper›PMID 29968796›Full record

ArticleScientific reports2018

ChemDIS-Mixture: an online tool for analyzing potential interaction effects of chemical mixtures.

Chun-Wei Tung, Chia-Chi Wang, Shan-Shan Wang, Pinpin Lin

Abstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2023
    Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. ChemDIS 2: an update of chemical-disease inference system.Database : the journal of biological databases and curation · 2018
    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

4 authors.

Chun-Wei TungSchool of Pharmacy, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan. cwtung@kmu.edu.tw.ORCID 0000-0003-3011-8440
Chia-Chi WangSchool of Pharmacy, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.
Shan-Shan WangSchool of Pharmacy, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.
Pinpin LinNational Institute of Environmental Health Sciences, National Health Research Institutes, Miaoli County, 35053, Taiwan. pplin@nhri.org.tw.

Funding

Ministry of Science and Technology, Taiwan (Ministry of Science and Technology of Taiwan) MOST104-2221-E-037-001-MY3
6 · The paper itself

Abstract

The assessment of bioactivity and toxicity for mixtures remains a challenging work. Although several computational models have been developed to accelerate the evaluation of chemical-chemical interaction, a specific biological endpoint should be defined before applying the models that usually relies on clinical and experimental data. The development of computational methods is desirable for identifying potential biological endpoints of mixture interactions. To facilitate the identification of potential effects of mixture interactions, a novel online system named ChemDIS-Mixture is proposed to analyze the shared target proteins, and common enriched functions, pathways, and diseases affected by multiple chemicals. Venn diagram tools have been implemented for easy analysis and visualization of interaction targets and effects. Case studies have been provided to demonstrate the capability of ChemDIS-Mixture for identifying potential effects of mixture interactions in clinical studies. ChemDIS-Mixture provides useful functions for the identification of potential effects of coexposure to multiple chemicals. ChemDIS-Mixture is freely accessible at http://cwtung.kmu.edu.tw/chemdis/mixture .

Identifiers

PMID29968796
PMCPMC6030136

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Registered trials

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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.