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Deep learning algorithms reveal the rules of gene regulation With the help of artificial intelligence (AI) a German-American team of scientists deciphered some of the more elusive instructions encoded in DNA. Their neural network trained on high-resolution maps of protein-DNA interactions uncovers subtle DNA sequence patterns throughout the genome, thus providing a deeper understanding of how these sequences are organized to regulate genes.

Artificial intelligence (AI) is seen as a key technology with fields of application in a wide variety of areas in society. However, researching, developing and, in particular, using AI systems presents enormous challenges for the computing power and storage capacity needed to process large data volumes.

Spatial and temporal distribution of primordial germ cells (stained in red) in zebrafish embryos. Normally, with the help of an attractant produced in the environment, the cells migrate in a targeted and coordinated manner through the developing embryo and reach the regions where the sex organs are formed (left).

In the digital age, data traffic is growing at an exponential rate. The demands on computing power for applications in artificial intelligence such as pattern and speech recognition in particular, or for self-driving vehicles, often exceeds the capacities of conventional computer processors. Working together with an international team, researchers at the University of Münster are developing new approaches and process architectures which can cope with these tasks extremely efficient.

Fans are not amused about decisions made by video assistants Since the 2019/20 season, controversial referee calls in the English Premier League may be technically reviewed and, if deemed necessary, corrected. Using a Twitter analysis of 129 games in the English Premier League, a research team from the Technical University of Munich (TUM) has now determined how decisions made by video referees affect the mood of the fans.

In a recent nature perspective, international experts in the field of optical neural networks, optical deep learning and photonic computing have put their expertise together to review the path from pathbreaking optical neural networks and optical computing realizations in the past fifty years and how they advanced to photonic artificial intelligence applications.

A new image processing programme makes it possible to view and analyse plant cells in detail in 3D. Bioscientists and computer scientists at Heidelberg University helped to develop the open-source software called PlantSeg. It is based on methods of machine learning and can be used to study the process of morphogenesis - how the shape of plants develops - at the cellular level.

Bioinformaticians at the University of Jena develop new method for analysing metabolites Everything that lives has metabolites, produces metabolites and consumes metabolites. These molecules arise as intermediate and end products from chemical processes in an organism's metabolism. Therefore, they not only have huge significance for our lives, but they also provide valuable information about the condition of a living being or an environment.

Novel deep learning method enables clinic-ready automated screening for diabetes-related eye disease Researchers created a novel deep learning method that makes automated screenings for eye diseases such as diabetic retinopathy more efficient. Reducing the amount of expensive annotated image data that is required for the training of the algorithm, the method is attractive for clinics.

Intelligent software for a better understanding of plant tissue development Using artificial intelligence, researchers have developed a novel computer-based image processing method for plant sciences. The method enables the detailed 3D representation of all cells in various plant organs with unprecedented precision.

Security software for autonomous vehicles Before autonomous vehicles participate in road traffic, they must demonstrate conclusively that they do not pose a danger to others. New software developed at the Technical University of Munich (TUM) prevents accidents by predicting different variants of a traffic situation every millisecond.

Genetic material as a stable storage medium "Biohackers" TV series stored on DNA The first episode of the newly released series "Biohackers" was stored in the form of synthetic DNA. This was made possible by the research of Prof. Reinhard Heckel of the Technical University of Munich (TUM) and his colleague Prof. Robert Grass of ETH Zürich.

Participants are needed for a study being conducted by Freie Universität, the Fraunhofer Institute for Applied and Integrated Security (AISEC), the Fraunhofer Institute for Secure Information Technology (SIT), and the National Research Center for App No 137/2020 from Aug 13, 2020 Researchers from Freie Universität, the Fraunhofer Institute for Applied and Integrated Security (AISEC), the Fraunhofer Institute for Secure Information Technology (SI

National research data infrastructure: TUM involved in three consortia Genome sequencing produces immense quantities of data. The aim of the German Human Genome-Phenome Archive (GHGA) is to make these data available to science without violating the personality rights of patients. The GHGA will focus initially on data collections pertaining to cancer and rare genetic disorders.

Landing a helicopter on the deck of a ship in poor visibility is a big challenge even for the most experienced of pilots. Researchers at the Technical University of Munich (TUM) have developed an assistance system that displays key information in the visor of the pilot's helmet-mounted display. This permits precise landing approaches - even in adverse weather conditions.

Open-source platform "VirtualFlow" examines billions of molecules in a very short time / Joint press release issued by Freie Universität Berlin and Technische Universität Berlin No 071/2020 from Apr 29, 2020 The development of new active compounds in medicine can take many years and potentially cost billions of euros.

The University of Stuttgart will be the first European institution to join the AI Horizons Network of IBM in order to advance AI research on the interaction of language and knowledge as part of a multi-year cooperation. The AI Horizons Network is a global network of researchers and doctoral students founded by IBM to further develop the use of artificial intelligence, machine learning, natural language processing, and related technologies in a series of research projects and experiments.

Currently, the corona pandemic is dominating the entire social life in Germany and in many other parts of the world. We are working flat out in order to better help the more than one hundred thousand seriously ill people in hospitals. One promising approach to extending current treatment methods is to use existing and approved drugs to combat the virus.

In the fight against Covid-19, an interdisciplinary research team at the Technical University of Munich (TUM) has developed a model for a contact tracing app that protects personal data. The concept is based on an encryption process that prevents the temporary contact numbers (TCNs) of infected individuals from ending up on the phones of their contacts.

Everyday life without artificial intelligence is barely conceivable in today's world. Countless applications in areas such as autonomous driving, foreign language translations or medical diagnostics have found their way into our lives. In chemical research, too, great efforts are being made to apply artificial intelligence (AI), also known as machine learning, effectively.