Technical University of Munich (TUM)
Technische Universität München (TUM)

Germany

The Technical University of Munich (TUM) is one of Europe’s leading universities in science and technology, and one of Germany’s Universities of Excellence. With our research agenda “human-centered engineering“ we put people and their lives at the heart of our scientific endeavours – whether we are investigating the origins of life, matter and the universe, or looking for solutions to the major challenges for our society.

Research news

Latest top-level research from a broad range of subjects that is unparalleled in continental Europe: www.tum.de/news

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International rankings regularly place TUM among the top universities in Germany and in Europe. Rankings

Our agenda: Human-centered research and innovation

We are seeking to understand the essential foundations of life, to maintain health and target diseases, and to shape a sustainable living enviroment. We are creating new materials and advanced manufacturing technologies, we are pioneering the digital transformation for a secure future – and are above all committed to responsible research and innovation in service of society.
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Portrait: Technical University of Munich – 150 Years culture of excellence

1 October 2019 - 30 September 2020

Region: Global
Subject/journal group: All

The table to the right includes counts of all research outputs for Technical University of Munich (TUM) published between 1 October 2019 - 30 September 2020 which are tracked by the Nature Index.

Hover over the donut graph to view the FC output for each subject. Below, the same research outputs are grouped by subject. Click on the subject to drill-down into a list of articles organized by journal, and then by title.

Note: Articles may be assigned to more than one subject area.

Count Share
617 164.64

Outputs by subject (Share)

Subject Count Share
Chemistry 149 63.28
Physical Sciences 279 61.54
Life Sciences 231 42.74
Earth & Environmental Sciences 25 8.60

Highlight of the month

Forecasting the future state of cells with AI

© MR.Cole_Photographer/Getty

© MR.Cole_Photographer/Getty

AI modelling of gene dynamics in single cells could be used to predict how individual cells will develop.

RNA velocity is the speed at which the expression of each gene in a cell is increasing or decreasing at a given moment. Conventional single-cell sequencing methods measure it only from static snapshots, limiting its use for predicting how a cell will develop.

Now, a team led by researchers at the Technical University of Munich has created an open-access AI model called scVelo to estimate the RNA velocity of dynamic biological systems.

They used machine learning methods to teach scVelo the likelihood of every possible way a gene could act at any point during a cell’s development. The team used scVelo to analyse cell development in the mouse pancreas and in regenerating human lung tissues.

scVelo could be used to study cellular responses to disease progression and cancer treatment.

Supported content

  1. Nature Biotechnology 38, 1408–1414 (2020). doi: 10.1038/s41587-020-0591-3

View the article on the Nature Index

See more research highlights from Technical University of Munich (TUM)

More research highlights from Technical University of Munich (TUM)

1 October 2019 - 30 September 2020

International vs. domestic collaboration by Share

  • 40.13% Domestic
  • 59.87% International

Note: Hover over the graph to view the percentage of collaboration.

Note: Collaboration is determined by the fractional count (Share), which is listed in parentheses.

Affiliated joint institutions and consortia

Return to institution outputs