Often focusing on the brain, we characterize gene networks using functional genomics data to generate insight into diverse levels of activity, typically starting with regulatory interactions and moving up to more diffuse associations important for understanding systemic dynamics.
Primary Appointment to Physiology
Cross-Appointment to Donnelly Centre for Cellular & Biomolecular Research
Research Divisions: Brain Research and Integrated Neurophysiology
Research Interests: Research in my lab aims to understand the flow of information from the genome to whole organism biology through modeling and analysis of functional genomics data. This research is broadly integrative across modalities, systems, and even species but also integrative across levels of organization, using molecular processes within cells to understand how and why cells diversify and how that diversity in turn affects organism phenotype. Because of its complex phenotype at both the cellular and organismal level, we particularly focus on the brain. A common approach within my lab is the analysis of gene co-expression, or the shared expression profile of genes across conditions. Genes which express under similar conditions will tend to share functions, and by tailoring data and methods, this can usefully model biological systems from cells to organisms to species.
Keywords: Co-expression, Single cell, RNA-seq, Gene expression, Machine learning, Bioinformatics, Gene networks, Cross-species, Model systems, Stochasticity, Neuroscience, Development
For a full list of publications, please see: https://scholar.google.com/citations?user=N7GhB1IAAAAJ&hl=en
A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex
Z Yao, H Liu, F Xie, S Fischer, RS Adkins, AI Aldridge, SA Ament, ...
Nature 2021; 598 (7879), 103-110
Assessing the replicability of spatial gene expression using atlas data from the adult mouse brain
S Lu, C Ortiz, D Fürth, S Fischer, K Meletis, A Zador, J Gillis
PLoS biology 2021; 19 (7), e3001341
Single-cell co-expression analysis reveals that transcriptional modules are shared across cell types in the brain
BD Harris, M Crow, S Fischer, J Gillis
Cell Systems 2021.
How many markers are needed to robustly determine a cell's type?
S Fischer, J Gillis
iScience 2021; 24 (11), 103292
Scaling up reproducible research for single-cell transcriptomics using MetaNeighbor
S Fischer, M Crow, BD Harris, J Gillis
Nature Protocols 2021; 16 (8), 4031-4067