SIB Remarkable Outputs 2023
The Swiss Institute of Bioinformatics (SIB) released a shortlist of outstanding works produced during the year 2023 by their members. The list is featuring an output from the Biomedical Informatics Group led by Gunnar Rätsch, in collaboration with the Learning & Adaptive Systems Group led by Andreas Krause.
Each year, the Swiss Institute of Bioinformatics releases a list of the best achievements and work produced by their scientists over the last year. These outputs, selected by the SIB Award Committee, can include peer-reviewed publications, preprints, resources, software tools, databases, outreach programmes and science advocacy, among others.
This year's SIB Remarkable Outputs 2023 features work from the Department of Computer Science. The paper titled "Learning Single-Cell Perturbation Responses using Neural Optimal Transport", from the Biomedical Informatics Group, led by Professor Gunnar Rätsch, in collaboration with the Learning & Adaptive Systems Group, led by Professor Andreas Krause, is being honoured for making "a significant step forward in terms of understanding the heterogeneous response of different cell states to environmental perturbations. It may impact drug discovery in the future.”
In their work, the researchers propose CellOT, a framework to model single-cell perturbation responses from unpaired treated and untreated cell states using neural optimal transport. By adequately modeling the nature of the problem through the lens of optimal transport, CellOT determines how perturbations affect cellular properties, reconstructs the most likely trajectory that single cells take upon perturbation and subsequently assists in a better understanding of driving factors of cell-fate decision and cellular evasion mechanisms.
Further information
- Gunnar Rätsch
- Biomedial Informatics Lab
- Andreas Krause
- Learning & Adaptive Systems Group
- external page Learning Single-Cell Perturbation Responses using Neural Optimal Transport
- external page SIB Remarkable Outputs 2023
- external page SIB Swiss Institute of Bioinformatics