CBG, ETH Zurich
@cbg.ethz.ch
Computational Biology Group in D-BSSE, @ethzurich.bsky.social, led by Niko Beerenwinkel.
https://bsse.ethz.ch/cbg/
https://bsse.ethz.ch/cbg/
Reposted by CBG, ETH Zurich
Minimising biases in #viralsurveillance data from #wastewater: A study led by the groups of Niko Beerenwinkel and Tanja Stadler @ethz.ch as well as their collaborators at @eawag.bsky.social developed a mathematical tool to factor in 'shedding' >https://u.ethz.ch/zUQBP
September 23, 2025 at 9:25 AM
Minimising biases in #viralsurveillance data from #wastewater: A study led by the groups of Niko Beerenwinkel and Tanja Stadler @ethz.ch as well as their collaborators at @eawag.bsky.social developed a mathematical tool to factor in 'shedding' >https://u.ethz.ch/zUQBP
We’re happy to announce our study on tracing influenza A from wastewater has been published in Water Research. We developed a novel tiling amplicon approach, enabling deep genomic coverage and our method is now part of Swiss-wide wastewater surveillance efforts.
www.sciencedirect.com/science/arti...
www.sciencedirect.com/science/arti...
Characterizing influenza A virus lineages and clinically relevant mutations through high-coverage wastewater sequencing
Influenza A virus poses significant public health challenges, causing seasonal outbreaks and pandemics. Its rapid evolution motivates continuous monit…
www.sciencedirect.com
September 23, 2025 at 7:51 AM
We’re happy to announce our study on tracing influenza A from wastewater has been published in Water Research. We developed a novel tiling amplicon approach, enabling deep genomic coverage and our method is now part of Swiss-wide wastewater surveillance efforts.
www.sciencedirect.com/science/arti...
www.sciencedirect.com/science/arti...
www.nature.com/articles/s41...
In our new study, we use mathematical modelling, simulations, and Swiss wastewater data to show that that key epidemiological metrics are not biased by differences in virus shedding. This highlights the robustness of wastewater monitoring for pathogen surveillance.
In our new study, we use mathematical modelling, simulations, and Swiss wastewater data to show that that key epidemiological metrics are not biased by differences in virus shedding. This highlights the robustness of wastewater monitoring for pathogen surveillance.
Estimated transmission dynamics of SARS-CoV-2 variants from wastewater are unbiased and robust to differential shedding - Nature Communications
Epidemiological estimates from wastewater are not biased by testing rates but may be subject to other biases. Here, the authors investigate the impact of variable virus shedding profiles for different...
www.nature.com
August 14, 2025 at 2:09 PM
www.nature.com/articles/s41...
In our new study, we use mathematical modelling, simulations, and Swiss wastewater data to show that that key epidemiological metrics are not biased by differences in virus shedding. This highlights the robustness of wastewater monitoring for pathogen surveillance.
In our new study, we use mathematical modelling, simulations, and Swiss wastewater data to show that that key epidemiological metrics are not biased by differences in virus shedding. This highlights the robustness of wastewater monitoring for pathogen surveillance.
Congratulations to Xiang Ge Luo for the Outstanding Student Paper award at ISMB/ECCB 2025 in Liverpool (www.iscb.org/ismbeccb2025...) for her work on the Bayesian inference of fitness landscapes via tree-structured branching processes published in Bioinformatics at doi.org/10.1093/bioi...
July 25, 2025 at 3:18 PM
Congratulations to Xiang Ge Luo for the Outstanding Student Paper award at ISMB/ECCB 2025 in Liverpool (www.iscb.org/ismbeccb2025...) for her work on the Bayesian inference of fitness landscapes via tree-structured branching processes published in Bioinformatics at doi.org/10.1093/bioi...
We are excited to share our latest research published in Nature Genetics, where we could detect genetic heterogeneity within circulating tumor cell clusters that can seed metastases. To do so, we tailor-made a new phylogenetic algorithm "CTC-SCITE": www.nature.com/articles/s41...
Phylogenetic inference reveals clonal heterogeneity in circulating tumor cell clusters - Nature Genetics
Phylogenetic analyses in patients with cancer and xenograft models highlight heterogeneity within individual CTC clusters, providing insights into clonal dynamics during metastasis.
www.nature.com
June 2, 2025 at 10:15 AM
We are excited to share our latest research published in Nature Genetics, where we could detect genetic heterogeneity within circulating tumor cell clusters that can seed metastases. To do so, we tailor-made a new phylogenetic algorithm "CTC-SCITE": www.nature.com/articles/s41...