EuroBioC 2022 conference, Heidelberg, BioQuant, September 14-16, 2022.
Where Software and Biology Connect
EuroBioC 2022 conference, Heidelberg, BioQuant, September 14-16, 2022.
Current developments within and beyond the Bioconductor project
EuroBioC 2022 conference, Heidelberg, BioQuant, September 14-16, 2022.
Workshops, keynote presentations, and more
Submission is open!
Registration for the EuroBioC2022 in-person conference will open May 20, 2022.
Venue: Germany, Heidelberg, Center for Quantitative Analysis of Molecular and Cellular Biosystems (BioQuant)
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Speakers
Dr. Shila Ghazanfar
Research Associate in Statistical Bioinformatics, Cancer Research UK Cambridge Institute
Dr. Ghazanfar obtained her PhD in statistics from the University of Sydney. For postdoctoral research, she joined the Cancer Research UK Cambridge Institute, with a keen interest in interdisciplinary and collaborative research. She will be starting a Discovery Early Career Researcher Award (DECRA) at the University of Sydney in 2022. Shila develops statistical and computational methods for understanding cellular heterogeneity and interaction using spatial genomics at single cell resolution and leveraging non-spatial single cell data sources. https://shazanfar.github.io/, https://twitter.com/shazanfar
Dr. Michael Dorrity
Group Leader, EMBL
Michael Dorrity has a PhD in Biology from the University of Washington (UW), Seattle. He did postdoctoral research with Cole Trapnell in the Department of Genome Sciences at UW, applying single-cell genomic and statistical approaches to dissect the effects of temperature in individual developing zebrafish embryos. He joined EMBL in Heidelberg as Group leader in January 2022, aiming to understand mechanisms of developmental robustness in the face of a changing environment using modern single-cell technologies and computational methods. https://www.embl.org/groups/dorrity/, https://twitter.com/mwdorr
Dr. Judith Zaugg
Group Leader, EMBL
Dr. Zaugg is a group leader at EMBL, where she investigates the variation of molecular phenotypes among individuals along with their genetic and epigenetic variation with the aim of better understanding the molecular basis of complex genetic diseases and inter-individual differences in drug response. She applies and develops computational biology tools for integrating large-scale biological ‘omics data to address questions in personalised genomics and investigate basic gene regulatory mechanisms. Dr. Zaugg obtained her undergraduate training in systems biology at the ETH Zurich and her PhD at the University of Cambridge / EMBL-EBI on computational biology of epigenetics and nuclear organization. She did postdoctoral research with Mike Snyder at the Department of Genetics at Stanford University. https://www.zaugg.embl.de/, https://twitter.com/zauggj
Dr. Björn Grüning
Galaxy team leader, University of Freiburg
Björn Grüning works at the Institute of Computer Science, University of Freiburg. He leads the Freiburg Galaxy team, which supports scientists with NGS data analyses (RNA-seq, ChIP-seq, exome-seq, methylC-seq), genome annotation for eukaryotic and prokaryotic organisms (from gene prediction to functional description), proteomics and metabolomics analysis, and the ChemicalToolBoX for analysis of small compounds. Galaxy has a huge variety of data visualization tools, over 800 different analysis tools, and ready-to-use pipelines for different applications. After registration, all tools and the infrastructure for data analysis are freely available and can be used for creation of your own workflows for your specific projects. https://twitter.com/bjoerngruening
Dr. Gioele La Manno
Neurodevelopmental Systems Biology Lab, EPFL
Gioele La Manno earned his PhD at Karolinska Institutet, working with Sten Linnarsson. Trained in biotechnology and biomedicine, his research now encompasses molecular biology, computational biology and bioinformatics, and focuses on understanding brain development. He is particularly interested in describing the sequence of states that embryonic stem cells go through during their differentiation towards mature neurons. He has been tackling this question using machine learning tools on the wealth of data provided by single cell RNA sequencing, a technique he has been working with and developing since its early times. https://gioelelamanno.com/people/gioelelamanno/, https://twitter.com/GioeleLaManno
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