ArticleRoyal Society open science2020
An integrative machine learning approach to discovering multi-level molecular mechanisms of obesity using data from monozygotic twin pairs.
Article in Royal Society open science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
7 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A Systematic Review on Applications of Artificial Intelligence for Obesity Prevention.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2026Pooled it
- Systematic Review of Machine Learning applied to the Prediction of Obesity and Overweight.Journal of medical systems · 2023Pooled it
- Study of the Genetic Basis of Childhood and Adolescent Obesity with Stress Through the Analysis of Multidimensional Data with Machine Learning and Artificial Intelligence Tools.Advances in experimental medicine and biology · 2026Article
- Obesity Biomarkers: Exploring Factors, Ramification, Machine Learning, and AI-Unveiling Insights in Health Research.MedComm · 2025Review
- Harnessing Artificial Intelligence in Obesity Research and Management: A Comprehensive Review.Diagnostics (Basel, Switzerland) · 2025Review
- A proteogenomic analysis of the adiposity colorectal cancer relationship identifies GREM1 as a probable mediator.International journal of epidemiology · 2024Article
- Applications of Artificial Intelligence to Obesity Research: Scoping Review of Methodologies.Journal of medical Internet research · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We combined clinical, cytokine, genomic, methylation and dietary data from 43 young adult monozygotic twin pairs (aged 22-36 years, 53% female), where 25 of the twin pairs were substantially weight discordant (delta body mass index > 3 kg m
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.