Network methodologies for understanding gene coexpression in the human brain.

Abstract

The PhD student will investigate algorithmic and statistical methodologies for improving the reliability, testability, causal inferability, and extensibility of gene co-expression networks. These methodologies will be applied to and validated within a multi-disciplinary cross-college collaboration that for several years has been working on improving our understanding of the regulation of gene expression in multiple regions of the human brain.





References:
[1]

Ramasamy A, Trabzuni D, Guelfi S, Varghese V, Smith C, Walker R, De T; UK Brain Expression Consortium; North American Brain Expression Consortium, Coin L, de Silva R, Cookson MR, Singleton AB, Hardy J, Ryten M, Weale ME. Genetic variability in the regulation of gene expression in ten regions of the human brain. Nat Neurosci. 2014 Oct;17(10):1418-28. doi: 10.1038/nn.3801. Epub 2014 Aug 31. PMID: 25174004.

[2]

Forabosco P, Ramasamy A, Trabzuni D, Walker R, Smith C, Bras J, Levine AP, Hardy J, Pocock JM, Guerreiro R, Weale ME, Ryten M. Insights into TREM2 biology by network analysis of human brain gene expression data. Neurobiol Aging. 2013 Dec;34(12):2699-714. doi: 10.1016/j.neurobiolaging.2013.05.001. Epub 2013 Jul 12. PMID: 23855984

[3]

Bettencourt C, Ryten M, Forabosco P, Schorge S, Hersheson J, Hardy J, Houlden H; United Kingdom Brain Expression Consortium. Insights from cerebellar transcriptomic analysis into the pathogenesis of ataxia. JAMA Neurol. 2014 Jul 1;71(7):831-9. doi: 10.1001/jamaneurol.2014.756. PMID: 24862029

[4]

Langfelder P, Luo R, Oldham MC, Horvath S (2011) Is my network module preserved and reproducible? PloS Comp Biol. 7(1): e1001057


Biological Areas:

Neurobiology
Genetics

BBSRC Area:

Genes, development and STEM approaches to biology