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 Sara Mostafavi

Talk Title:
“Using genomics data to infer mechanistic models for complex phenotypes”

Thursday, March 10, 2016 6:00pm

Assistant Professor, Departments of Statistics & Medical Genetics, University of British Columbia (UBC)

Web-site: Sara Mostafavi
Twitter: @sara_mostafavi

Technological advances in the last decade now enable us to measure parts of biological systems at various resolutions, for example, at the genome, epigenome, and the transcriptome levels. These data provide an opportunity to build mechanistic models of gene regulatory networks, and further to infer dysregulation of these networks that underlie complex diseases and traits. In this talk, I’ll present computational and statistical approaches for: a) combining multiple types of genomics data to better understand dysregulatory effects in a complex psychiatry disorder, namely major depression; b) inferring gene regulatory networks across multiple tissues and cell types, and identifying the impact of inter-individual genetic variation on these networks.

Sara Mostafavi is an Assistant Professor at the Departments of Statistics and Medical Genetics at UBC. Sara did her PhD in Computer Science at the University of Toronto, where she focused her research in the area of machine learning and computational biology. She then did a postdoctoral fellowship at Stanford’s Department of Computer Science, followed by a research fellowship at Harvard Medical School. Sara’s research focuses on developing and using machine learning and statistical methods for combining high dimensional genomics data, in order to reconstruct gene regulatory networks, and to identify genes and pathways underlying a variety of complex neuropsychiatric disorders.

Please note:
Trainees are invited to meet with the VanBUG speaker for open discussion of both science and career paths. This takes place 4:30-5:30pm in either the Boardroom or Lunchroom on the ground floor of the BCCRC

Recommended Readings

  1. Mostafavi S, et al. Type I interferon signaling genes in recurrent major depression: increased expression detected by whole-blood RNA sequencing. Mol Psychiatry. 2014 Dec;19(12):1267-74.
  2. Battle A, Mostafavi S, et al. Characterizing the genetic basis of transcriptome diversity through RNA-sequencing of 922 individuals. Genome Res. 2014 Jan;24(1):14-24.
  3. Pierson E, GTEx Consortium, Koller D, Battle A, Mostafavi S et al. Sharing and Specificity of Co-expression Networks across 35 Human Tissues. PLoS Comput Biol. 2015 May 13;11(5)


Introductory Speaker:
Elizabeth Chun (PhD Student, Dr. Marco Marra’s Lab, BCCRC)

“Heterogeneous epigenetic landscape of extra-cranial malignant rhabdoid tumours”


Webcast Link:
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