Evidence map›Paper›PMID 20346093›Full record

ArticleGenome medicine2010

Simulating gene-environment interactions in complex human diseases.

Bo Peng

Abstract read
In one paragraph

Article in Genome medicine, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

1 author.

Bo PengDepartment of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. bpeng@mdanderson.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Because little is currently known about how genes interact with environmental factors in human diseases, and because of the large number of possible interactions between and within genetic and environmental factors, it is difficult to simulate samples for a disease caused by multiple interacting genetic and environmental factors. A recent article by Amato and colleagues in BMC Bioinformatics describes a mathematical model to characterize gene-environment interactions and a computer program that simulates them using biologically meaningful inputs. Here, I evaluate the advantages and limitations of the authors' approach in terms of its usefulness for simulating genetic samples for real-world studies of gene-environment interactions in complex human diseases.

Identifiers

PMID20346093
PMCPMC2873799

What OpenQuestion holds

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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.