ArticlePloS one2011
A network of genes, genetic disorders, and brain areas.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Application of Graph Theory to Assess Static and Dynamic Brain Connectivity: Approaches for Building Brain Graphs.Proceedings of the IEEE. Institute of Electrical and Electronics Engineers · 2018Article
- Bipartite graphs in systems biology and medicine: a survey of methods and applications.GigaScience · 2018Review
- Protein interaction network constructing based on text mining and reinforcement learning with application to prostate cancer.IET systems biology · 2015Article
- Application and evaluation of automated methods to extract neuroanatomical connectivity statements from free text.Bioinformatics (Oxford, England) · 2012Article
- Using text mining to link journal articles to neuroanatomical databases.The Journal of comparative neurology · 2012Article
- A Bayesian analysis of the chromosome architecture of human disorders by integrating reductionist data.Scientific reports · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
The network-based approach has been used to describe the relationship among genes and various phenotypes, producing a network describing complex biological relationships. Such networks can be constructed by aggregating previously reported associations in the literature from various databases. In this work, we applied the network-based approach to investigate how different brain areas are associated to genetic disorders and genes. In particular, a tripartite network with genes, genetic diseases, and brain areas was constructed based on the associations among them reported in the literature through text mining. In the resulting network, a disproportionately large number of gene-disease and disease-brain associations were attributed to a small subset of genes, diseases, and brain areas. Furthermore, a small number of brain areas were found to be associated with a large number of the same genes and diseases. These core brain regions encompassed the areas identified by the previous genome-wide association studies, and suggest potential areas of focus in the future imaging genetics research. The approach outlined in this work demonstrates the utility of the network-based approach in studying genetic effects on the brain.
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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.