News

“scifi-RNA-seq” method for ultra-high-throughput RNA sequencing in single cells

30/05/21

Molecular analysis of single cells provides an important basis for precision medicine. Five years ago, scientists around the world came together to pursue the “Human Cell Atlas” project, with the aim of cataloging all cells in the human body. These data have helped, for example, to identify those cell types that the coronavirus can infect particularly well. To accelerate and improve the creation of such cell catalogs, Paul Datlinger and André F. Rendeiro from Christoph Bock’s research group at CeMM developed a new method that enables single-cell RNA sequencing in a very large number of individual cells at the same time.

Blood test detects childhood tumors based on their epigenetic profiles

27/05/21

A new study exploits the characteristic epigenetic signatures of childhood tumors to detect, classify and monitor the disease. The scientists analyzed short fragments of tumor DNA that are circulating in the blood. These "liquid biopsy" analyses exploit the unique epigenetic landscape of bone tumors and do not depend on any genetic alterations, which are rare in childhood cancers. This approach promises to improve personalized diagnostics and, possibly, future therapies of childhood tumors such as Ewing sarcoma. The study has been published in Nature Communications.

Mutational Dynamics of SARS-CoV-2 in Austria: UK and South Africa variants found in Austria

03/01/21

Over the last few weeks, the United Kingdom and South Africa have faced a rapid increase in COVID-19 cases leading to enhanced epidemiological and virological investigations. Analysis of viral genome sequence data identified a sizeable proportion of cases belonging to new phylogenetic clusters. The new SARS-CoV-2 variants are defined by nonsynonymous, several of which are found in the viral spike protein, and still of uncertain functional significance. While it is known that viruses constantly change through mutation, and seldom does it lead to biological changes, the variants now increasingly observed in the UK and South Africa may be associated with increased infectivity.

Christoph Bock becomes Professor of Medical Informatics at MedUni Vienna

31/12/20

Christoph Bock has been appointed as professor of medical informatics at the Medical University of Vienna and head of the Institute for Artificial Intelligence and Decision Support at CeMSIIS, starting 1 January 2021. The bioinformatician and genome researcher joins MedUni Vienna from the neighboring CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences. He will continue to lead his research group at CeMM, complementary to the new tasks at MedUni Vienna.

ERC Consolidator Grant awarded to CeMM Principal Investigator Christoph Bock

08/12/20

Congratulations to Christoph Bock, Principal Investigator at CeMM and Guest Professor at the Medical University of Vienna, for receiving a prestigious and well-endowed ERC Consolidator Grant of the European Research Council.

Thomas Krausgruber awarded the ÖGAI Karl Landsteiner Prize for Basic Research in Immunology 2020

03/12/20

Congratulations to Thomas Krausgruber, Senior Postdoctoral Fellow in Christoph Bock’s Group at CeMM, who has received the Karl Landsteiner Prize for Basic Research in Immunology 2020!

Austrian study provides deep insights into transmission and mutation properties of SARS-CoV-2

22/11/20

Learning from past SARS-CoV-2 outbreaks for future pandemic control. In the COVID-19 pandemic, 57 million people have already been infected worldwide. In the search for vaccines and therapies, a precise understanding of the virus, its mutations and transmission mechanisms is crucial. A recent study by the research group of Principal Investigator Andreas Bergthaler at the CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, in the renowned journal Science Translational Medicine, makes an important contribution to this. The high quality of epidemiological data in Austria, together with state-of-the-art virus genome sequencing, has supported unprecedented insights of the mutation behaviour and transmission of the SARS-CoV-2 virus.

Christoph Bock among the world's most highly-cited scientists in 2020

18/11/20

Every year the “Highly Cited Researchers” list provided by Clarivate Analytics recognizes the most influential researchers with highly-cited papers that rank in the top 1% by citation in different scientific fields. This year 39 researchers in the list are working in Austria. Among them, CeMM PI Christoph Bock, who has been included in the cross-field category, highlighting the interdisciplinary nature of his work.

New EU-funded Research Project “HCA|Organoid”: Toward a Single-Cell Atlas of Human Organoids for Biomedical Research

30/08/20

HCA|Organoid is a new EU research project that combines single-cell profiling and organoid technology to validate organoids as faithful models of human biology. The project seeks to kickstart the development of an open access “Organoid Cell Atlas”. By creating well-characterized in vitro models of human organs, this resource will enable future discovery-driven and translational research on rare genetic diseases, complex multifactorial diseases, and on cancer. Toward this goal, Europe’s leading organoid researchers as well as experts in single-cell sequencing, single-cell imaging, and computational data integration have teamed up. The HCA|Organoid project is one of six pilot actions funded by the EU Horizon 2020 Framework Program that will constitute European contributions to the “Human Cell Atlas” – an ambitious global initiative striving to advance biomedical research and therapy using single-cell technologies. The HCA|Organoid consortium comprises eight partners and will receive EUR 5 million in EU funding.

Deep learning on cell signaling networks establishes interpretable AI for single-cell biology

03/08/20

Researchers at CeMM, the Research Center for Molecular Medicine of the Austrian Academy of Sciences, have developed knowledge-primed neural networks (KPNNs), a new method that combines the power of deep learning with the interpretability of biological network models. KPNNs learn multiple layers of protein signaling and gene regulation from single-cell RNA-seq data, thereby providing a much-needed boost in our ability to convert massive single-cell atlas data into biological insights. These findings have now been published in the renowned scientific journal Genome Biology.