Studying the genome these days involves high-throughput assays, with the formidable datasets of microarrays now being superseded by the even more daunting data generated by massively-parallel sequencing. The limiting factor in these experiments is no longer the generation of data but rather their analysis. Lead by Dr Greally, our Division is focused on this rate-limiting step, creating a collaborative environment for innovative and powerful studies of the genome and epigenome in human disease. This Division also serves as the Departmental interface to other Einstein resources, such as the Center for Epigenomics and the Computational Genomics Core Facility. The Division is based in the Price Annex, in the ground floor of the Van Etten Building.
The Division currently consists of five full-time faculty:
Adam Auton. Dr Auton's group develops statistical and computational methods for understanding patterns of genetic variation. In particular, the group uses population genetic models for the estimation of recombination rates from samples of population genetic data. Current projects include the large scale analysis of next-generation sequencing data from a number of species, with the aim of understanding how differences in recombination between species have evolved. Visit the Auton lab for more information.
Aaron Golden. The Golden lab is interested in optimizing data analysis and knowledge discovery from contemporary genomic datasets, as has been successfully implemented in the astronomical sciences in particular via Virtual Observatory technologies. Specific research interests include accelerated clustering algorithms for ChIP-seq and microbiome/metatranscriptome studies, techniques to facilitate integrative and systems-level user exploration of genomic scale datasets, and the methodological interface between astrophysics and genomics. Visit the Golden lab for more information.
John M. Greally. The Greally lab has several integrated areas of research including molecular assay development and computational biology research, with application of these approaches to questions in basic and clinical epigenomics. Ongoing projects include the development of assays to allow in vivo imaging of mammalian X chromosome inactivation and assays to measure DNA assays and RNA:DNA hybrid formation genome-wide. Computational projects include the effects of DNA methylation on mutation in tumour development, while applied studies include DNA methylation dynamics during differentiation, its role in gene body transcriptional suppression, and studies of the epigenome in infection and cancer. Visit the Greally lab for more information.
Deyou Zheng. Dr Zheng's group develop bioinformatics methods for mining and interpreting high-throughput genomic and epigenomic data. The research of his group is mainly focused on two areas: (i) characterizing pseudogene generation, evolution, and function by comparative and functional genomics; (ii) deciphering regulatory networks of pluripotency and cell lineage specification by integrated analysis of ChIP-Seq and RNA-Seq data from human iPS cells or mouse ES cells. Visit the Zheng lab for more information.
Zhengdong Zhang. The research interests of Dr Zhang's lab are computational biology and bioinformatics, focusing on algorithm development, data integration, and software implementation. The biological systems currently under investigation are breast cancer metastasis and human aging. Visit the Zhang lab for more information.
Brent Calder and Andy McLellan lead the Genomics and Epigenomics informatics development teams respectively, and Joseph Hargitai coordinates the Division's high performance computing resources. Additional faculty recruitment is underway for our new Computational Genetics initiative in the Department of Genetics.
High Performance Computing
Together with ITS and Research Computing, the Division through Joseph Hargitai coordinates the Department's significant computational resources. Information on access to these resources may be found the computational resources page.