Lingfei will give a talk at the RECOMB/ISCB Conference on Regulatory & Systems Genomics titled “Scalable causal gene network inference from genetics of gene expression data”.
Husain has successfully defended his PhD thesis “Cross-tissue regulatory gene networks in coronary atherosclerosis” at Karolinska Institute. Congratulations and good luck in your future career!
A warm welcome to Pau Erola who joins us as a postdoctoral Research Fellow, having completed a PhD in Computer Engineering from the Universitat Rovira i Virgili and an MSc in Biomedicine from the Universitat de Barcelona.
Hassan has successfully defended his PhD thesis
“eQTL mapping and inherited risk enrichment analysis : a systems biology approach for coronary artery disease” at Karolinska Institute. Congratulations and good luck in your new postdoc career!
Update: Cell Systems has published an Editorial Preview of our paper.
Husain’s paper “Cross-Tissue Regulatory Gene Networks in Coronary Artery Disease” has been published in Cell Systems, the new flagship systems biology journal from Cell Press. In this paper we reconstructed and analyzed regulatory gene networks across 7 vascular and metabolic tissues using genotype and gene expression data sampled from more than 100 individuals. Here’s the graphical abstract:
Chris’ paper Functional transcription factor target discovery via compendia of binding and expression profiles has been published in Scientific Reports. Congrats Chris!
A preprint of Chris’s paper on “Functional transcription factor target discovery via compendia of binding and expression profiles” is available from the arXiv. In this paper we demonstrated that prediction of functional target genes responding to the silencing of a transcription factor (TF) can be improved by correlating a gene’s TF-binding and expression profiles across multiple experimental conditions.
A preprint written by Lingfei on “Detection of regulator genes and eQTLs in gene networks” is available from the arXiv. This is a review article/book chapter reviewing the main analytical methods and softwares to identify eQTLs and their associated genes, to reconstruct co-expression networks and modules, to reconstruct causal Bayesian gene and module networks, and to validate predicted networks in silico.
The Systems Genomics group at the Roslin Institute at the University of Edinburgh headed by Dr Tom Michoel develops and applies analytical methods and software to model the complex variations of traits and diseases between individuals using large-scale multi-omics data. We are currently seeking two highly motivated postdoctoral Research Fellows to join our team.
The first position is funded by Roslin Institute Strategic Grant Funding from the BBSRC and will focus on the development and implementation of novel analytical methods for reconstructing causal gene networks from multi-omics data. Specific areas of interest include the modelling of cross-sectional transcriptome time series, the joint modelling of cis- and trans-eQTL associations in regulatory module networks, and the integrative modelling of transcriptome and metabolome data. Newly developed methods will be validated on published and unpublished data from experimental collaborators. This position requires a very strong background in statistical modelling and computer programming. A PhD degree in physics, informatics, mathematics, statistics or engineering is essential, and previous experience in working with large-scale omics data is a plus. The position is available immediately and is initially funded until 2019, with possibility of extension (subject to renewal of the Roslin Institute Strategic Grant Funding).
The second position is funded by the NIH and is part of a collaboration with the Icahn Institute for Genomics and Multiscale Biology at the Icahn School of Medicine at Mount Sinai in New York, aimed at discovering novel diagnostics and therapies of molecular subcategories of coronary artery disease (CAD) patients, centred around the analysis of a unique dataset of genotype and RNA-sequencing data from seven disease-relevant tissues of 600 CAD patients. This position will focus in particular on reconstructing causal gene networks for specific phenotypic subcategories of patients, and validating these networks in the context of existing GWAS, regulatory genomics (e.g. ENCODE and RoadMap Epigenomics) and other relevant datasets. This position requires previous experience in working with large-scale omics data and a strong computer programming background. A PhD degree in a computational science (e.g. bioinformatics, statistical genetics, physics, informatics, mathematics, statistics or engineering) is desired. Candidates with a PhD degree in the life sciences are welcome to apply, provided they can demonstrate a strong proficiency in statistics and computer programming. The position is available immediately and is funded for two years.
Applications or informal queries regarding the positions should be addressed to Dr Tom Michoel – Tom.Michoel@roslin.ed.ac.uk.