ArticlePloS one2016
Comprehensive Map of Molecules Implicated in Obesity.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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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.
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Who cites it
14 citing papers in PubMed.
- Article
- A Data-Driven Approach to Construct a Molecular Map ofVaccines · 2023Article
- The Role of Molecular and Hormonal Factors in Obesity and the Effects of Physical Activity in Children.International journal of molecular sciences · 2022Review
- Article
- The status of causality in biological databases: data resources and data retrieval possibilities to support logical modeling.Briefings in bioinformatics · 2021Article
- Automated inference of Boolean models from molecular interaction maps using CaSQ.Bioinformatics (Oxford, England) · 2020Article
- Discovery and characterization of functional modules associated with body weight in broilers.Scientific reports · 2019Article
- Article
- Computational Systems Biology Approach for the Study of Rheumatoid Arthritis: From a Molecular Map to a Dynamical Model.Genomics and computational biology · 2018Article
- NFPscanner: a webtool for knowledge-based deciphering of biomedical networks.BMC bioinformatics · 2017Article
- Correlation of TLR4 and KLF7 in Inflammation Induced by Obesity.Inflammation · 2017Article
- A new method of finding groups of coexpressed genes and conditions of coexpression.BMC bioinformatics · 2016Article
- Correlation of A2bAR and KLF4/KLF15 with Obesity-Dyslipidemia Induced Inflammation in Uygur Population.Mediators of inflammation · 2016Article
- Quantifying a Systems Map: Network Analysis of a Childhood Obesity Causal Loop Diagram.PloS one · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Obesity is a global epidemic affecting over 1.5 billion people and is one of the risk factors for several diseases such as type 2 diabetes mellitus and hypertension. We have constructed a comprehensive map of the molecules reported to be implicated in obesity. A deep curation strategy was complemented by a novel semi-automated text mining system in order to screen 1,000 full-length research articles and over 90,000 abstracts that are relevant to obesity. We obtain a scale free network of 804 nodes and 971 edges, composed of 510 proteins, 115 genes, 62 complexes, 23 RNA molecules, 83 simple molecules, 3 phenotype and 3 drugs in "bow-tie" architecture. We classify this network into 5 modules and identify new links between the recently discovered fat mass and obesity associated FTO gene with well studied examples such as insulin and leptin. We further built an automated docking pipeline to dock orlistat as well as other drugs against the 24,000 proteins in the human structural proteome to explain the therapeutics and side effects at a network level. Based upon our experiments, we propose that therapeutic effect comes through the binding of one drug with several molecules in target network, and the binding propensity is both statistically significant and different in comparison with any other part of human structural proteome.
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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.