Single-Cell Gene Regulatory Networks
Event details
| Date | 03.07.2017 |
| Hour | 12:15 › 13:15 |
| Speaker | Prof. Stein Aerts, VIB/ KU Leuven Center for Brain & Disease Research, Campus Gasthuisberg, Leuven (B) |
| Location | |
| Category | Conferences - Seminars |
DISTINGUISHED LECTURE IN BIOLOGICAL ENGINEERING
Abstract:
Single-cell transcriptomics and single-cell epigenomics allow building cell atlases of any given tissue and infer the dynamics of cellular state transitions during developmental or disease trajectories.
In the first part of my talk I will describe a single-cell atlas of the ageing Drosophila brain, for which we profiled more than 30.000 single cells with Drop-seq and 10X Chromium. Using a new bioinformatics method we developed, called SCENIC (Single Cell rEgulatory Network Inference and Clustering), we identified transcription factors, networks, and cell states of glutamatergic, cholinergic, gabaergic, dopaminergic, and mushroom body neurons, as well as various glial cell types including astrocytes and perineural glia.
In the second part of my talk I will describe a single-cell ATAC-seq data set we generated in the Drosophila eye imaginal disc. Using another new bioinformatics method, called cisTopic, we overcome the sparsity of these data, identifying relevant regulatory programs and stable cell states in the normal tissue, as well as in a Drosophila tumour model. Altogether, I will discuss various examples and computational methods to trace genomic regulatory programs at single-cell resolution.
Bio:
Research positions:
Abstract:
Single-cell transcriptomics and single-cell epigenomics allow building cell atlases of any given tissue and infer the dynamics of cellular state transitions during developmental or disease trajectories.
In the first part of my talk I will describe a single-cell atlas of the ageing Drosophila brain, for which we profiled more than 30.000 single cells with Drop-seq and 10X Chromium. Using a new bioinformatics method we developed, called SCENIC (Single Cell rEgulatory Network Inference and Clustering), we identified transcription factors, networks, and cell states of glutamatergic, cholinergic, gabaergic, dopaminergic, and mushroom body neurons, as well as various glial cell types including astrocytes and perineural glia.
In the second part of my talk I will describe a single-cell ATAC-seq data set we generated in the Drosophila eye imaginal disc. Using another new bioinformatics method, called cisTopic, we overcome the sparsity of these data, identifying relevant regulatory programs and stable cell states in the normal tissue, as well as in a Drosophila tumour model. Altogether, I will discuss various examples and computational methods to trace genomic regulatory programs at single-cell resolution.
Bio:
Research positions:
- Associate Professor and Principal Investigator of the Laboratory of Computational Biology, School of Medicine, University of Leuven (2009-)
- Postdoc at VIB, Bassem Hassan lab (2005-2009), Leuven
- Visiting postdoc at Developmental Biology Institute of Marseille, Luminy (IBDML), Marseille, France (2006), with Denis Thieffry and Carl Herrmann
- PhD Bioinformatics, School of Engineering (ESAT), University of Leuven (2001-2004)
- Bioinformatician, Data4s Future Technologies NV (2000-2001)
- Assistant IT Project Leader Janssen Pharmaceutica, Johnson&Johnson (1999-2000)
- Visiting undergraduate researcher at the Center for Genomic Sciences, Cuernavaca, Mexico (Jul-Nov 1998), with Esperanza Mart’nez-Romero.
- PhD in Engineering (Bioinformatics), Department of Electrical Engineering ESAT-SCD, University of Leuven (2004)
- Advanced Studies in Applied Computer Science, University of Brussels (2002)
- Master in Bioscience Engineering (Molecular Biology), University of Leuven (1999)
Practical information
- Informed public
- Free
Organizer
Contact
- Institute of Bioengineering (IBI, Magali Masson)