Helmholtz Munich

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We develop novel computational tools powered by AI to accelerate discovery and translation. We apply cutting-edge computational methods to promote personalised health. Collaboratively, we develop predictive algorithms as well as mechanistic models to analyse molecular, imaging, and clinical data of human health and disease. We thus help to create innovative diagnostics and novel treatments for environmentally triggered diseases.

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We develop robust methods for analyzing big data to address key biomedical challenges and consolidate analytical approaches using innovative digital methods. In addition, we develop novel statistical methods for trans- ethnic meta-analysis, testing for pleiotropy, rare variant burden, testing, and polygenic risk score construction.

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We develop and translate AI technologies for biomedical problems by constructing deep-learning methods and combining them with more mechanistic modeling approaches. In addition, we steer the computational aspects of developing single-cell atlases in healthy and disease state to build AI-driven analytics platforms for multimodal data, in particular from genomics and diverse imaging modalities.

We develop novel computational methods for multiomic data integration of epigenomic, transcriptomic, proteomic and genetic data and advanced phenotypic/in vivo observations. In addition, we design novel approaches for efficient data combination across omics levels, maximizing the information yield across the multidimensional space of datar from genomics and diverse imaging modalities.

Doctor using ultrasound equipment screening of pregnant woman.

How AI is Revolutionizing Medicine

Computer systems can already independently analyze health data, learn from it and even derive therapy recommendations. Which opportunities this means for patients and what research needs to apply artificial intelligence in practice.

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Computational Health, July 22, 2024

In this interview, Dr. Vincent Fortuin explains their new approach for reliable AI.

Bavarian AI Council 2024 at Helmholtz Munich

Transfer, Computational Health, June 07, 2024

The "Bavarian AI Council," established by the Bavarian State Government, met on June 7, 2024, at Helmholtz Munich. The host was Prof. Fabian Theis, Director of the Computational Health Center at Helmholtz Munich and Co-Chair of the AI Council for…

Computational Health, May 16, 2024

An Interview with Dr. Eric Schulz about Foundation Models and Machine Psychology.

Artificial intelligence in humanoid head with neural network thinks. AI with Digital Brain is learning processing big data, analysis information. Face of cyber mind. Technology background concept.

Awards & Grants, Computational Health, April 18, 2024

A Synergy Unit, in which Helmholtz Munich is involved, will develop, deploy, and connect foundation models.

Transfer, Computational Health, April 16, 2024

In a new collaboration, the Computational Health Center at Helmholtz Munich has teamed up with the global pharmaceutical company Pfizer. The joint initiative, spanning three years, aims to leverage Pfizer's vast knowledge and accumulated data in…

Computational Health, April 10, 2024

An interview with Prof. Fabian Theis, Head of the Computational Health Center, and Prof. Bjoern Eskofier, Group Leader for Translational Digital Health. The researchers hosted the first Munich Health Foundation Model Symposium on April 10, 2024, at…

Munich Health Foundation Model Symposium_with black

Transfer, Computational Health, March 19, 2024

Helmholtz Munich is bringing together a wide range of experts to advance the development of foundation models focused on health research. The Munich Health Foundation Model Symposium, to be held on April 10, 2024, at the Helmholtz Munich Campus, aims…

Computational Health, IML, March 11, 2024

Prof. Zeynep Akata has been heading the newly founded Institute for Explainable Machine Learning since January 2024. Her research focuses on developing explainable machine learning models for vision and language tasks. From building an institute from…

Computational Health, ITG, February 28, 2024

Prof. Eleftheria Zeggini about equity, diversity and inclusion in science

New Research Findings, Diabetes, Computational Health, ITG, February 19, 2024

The genetic information in our cells harbors secrets about the risks, progression, and complications of many diseases. With hundreds of millions of patients worldwide, identifying and understanding genetic risk for type 2 diabetes is of particular…

Featured Publication, Computational Health, AIH, December 08, 2023

Therapeutic antibodies play a crucial role in treating diseases by modifying immune cells. Scientists from the Institute of AI for Health at Helmholtz Munich in collaboration with Roche present an open-source framework for comprehensive antibody…

Public Engagement, Computational Health, AIH, IML, December 01, 2023

Helmholtz Munich organized its first "Expert Hour" in the German Bundestag. With this new event format, Helmholtz Munich will regularly provide information on politically relevant health and research topics in the future and support work in the…

Awards & Grants, Computational Health, AIH, November 23, 2023

The application of artificial intelligence methods for the generation of antimicrobial peptides will be the subject of research in the Deep Optimised Generation of AntiMicrobial Peptide (DOG-AMP) project. The project will be carried out by Prof. Ewa…

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Computational Health, ITG, November 10, 2023

The first "Munich for Women in Science" event is dedicated to inspiring positive change for Women in Science. The event will be hosted by Helmholtz Munich and has been organized in collaboration with the Technical University Munich (TUM), the…

Environmental Health, LHI, Computational Health, ICB, November 07, 2023

The Human Cell Atlas (HCA) promises insights into ourselves, unraveling our cellular landscape.

Medicine doctor touching electronic medical record on tablet. DNA. Digital healthcare and network connection on hologram modern virtual screen interface, medical technology and network concept.

Awards & Grants, Computational Health, ICB, October 26, 2023

The European Research Council (ERC) today awarded 37 particularly well-funded Synergy Grants across Europe. One of these interdisciplinary research awards went to Julien Gagneur, Group Leader at Helmholtz Munich and Professor of Computational…

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Computational Health, ICB, IML, October 25, 2023

Artificial Intelligence (AI) is becoming increasingly crucial in medical research, and Helmholtz Munich is one of the world's leading institutions in this field. It can detect tumors as effectively as severe eye diseases.

Transfer, Computational Health, October 12, 2023

The AiChemist project has officially started in September 2023 Coordinated by Helmholtz Munich the project is an Innovative Doctoral Training Network funded with 3 million euros provided by the Marie Skłodowska-Curie Actions (MSCA-DN) within the EU…

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New Research Findings, Computational Health, ICB, October 09, 2023

ScPoli Enables Multi-Scale Representations of Cells and Samples

The increasing amount of data recorded in medical research can only lead to scientific breakthroughs and essential therapies for patients if interpreted and analyzed correctly.…

New Research Findings, Computational Health, Bioengineering, IBMI, October 02, 2023

Researchers at Helmholtz Munich and the Technical University of Munich have made significant progress in advancing high-resolution optoacoustic imaging for clinical use. Their innovative deep-learning framework, known as DeepMB, holds great promise…

Speaker Giving a Talk at Business Meeting.

24.07.2024

Cordelia Schmid

Host: Zeynep Akata
Title: Foundation Models in Computer Vision
Time: 11:30 (CEST)
Location: In person

25.07.2024

Andreas Raue

Host: Fabian Theis
Title: Applications of Systems Biology in Drug R&D
Time: 16:00 (CEST)
Location: Hybrid Seminar

29.07.2024

Yongqin Xian

Host: Zeynep Akata
Title: Improving vision-language model pretraining with self-distillation and location-aware captioner
Time: 11:00 (CEST)
Location: In-person

12.09.2024

Manolis Dermitzakis

Host: Ele Zeggini
Title: Tbd
Time: Tbd
Location: Tbd

Publications

2024 Nature Communications

Sheng, X. ; Nenseth, H.Z. ; Qu, S. ; Kuzu, O.F. ; Frahnow, T. ; Simon, L. ; Greene, S. ; Zeng, Q. ; Fazli, L. ; Rennie, P.S. ; Mills, I.G. ; Danielsen, H. ; Theis, F.J. ; Patterson, J.B. ; Jin, Y. ; Saatcioglu, F.

Author Correction: IRE1α-XBP1s pathway promotes prostate cancer by activating c-MYC signaling.

2024 Scientific Article in Communications Biology

Ghaffar, A. ; Akhter, T. ; Strømme, P. ; Misceo, D. ; Khan, A. ; Frengen, E. ; Umair, M. ; Isidor, B. ; Cogné, B. ; Khan, A.A. ; Bruel, A.L. ; Sorlin, A. ; Kuentz, P. ; Chiaverini, C. ; Innes, A.M. ; Zech, M. ; Baláž, M. ; Havránková, P. ; Jech, R. ; Ahmed, Z.M. ; Riazuddin, S.

Variants of NAV3, a neuronal morphogenesis protein, cause intellectual disability, developmental delay, and microcephaly.

2024 Scientific Article in Journal of Pediatrics, The

Kobayashi, E.S. ; Lotan, N.S. ; Schejter, Y.D. ; Makowski, C. ; Kraus, V. ; Ramchandar, N. ; Meiner, V. ; Thiffault, I. ; Farrow, E. ; Cakici, J. ; Kingsmore, S. ; Wagner, M. ; Rieber, N. ; Bainbridge, M.

Biallelic loss of function variants in SENP7 cause immunodeficiency with neurologic and muscular phenotypes.

2024 Scientific Article in Nature Genetics

Schmidt, A. ; Danyel, M. ; Grundmann, K. ; Brunet, T. ; Klinkhammer, H. ; Hsieh, T.C. ; Engels, H. ; Peters, S. ; Knaus, A. ; Moosa, S. ; Averdunk, L. ; Boschann, F. ; Sczakiel, H.L. ; Schwartzmann, S. ; Mensah, M.A. ; Pantel, J.T. ; Holtgrewe, M. ; Bösch, A. ; Weis, C. ; Weinhold, N. ; Suter, A.A. ; Stoltenburg, C. ; Neugebauer, J. ; Kallinich, T. ; Kaindl, A.M. ; Holzhauer, S. ; Bührer, C. ; Bufler, P. ; Kornak, U. ; Ott, C.E. ; Schülke, M. ; Nguyen, H.H.P. ; Hoffjan, S. ; Grasemann, C. ; Rothoeft, T. ; Brinkmann, F. ; Matar, N. ; Sivalingam, S. ; Perne, C. ; Mangold, E. ; Kreiss, M. ; Cremer, K. ; Betz, R.C. ; Mücke, M.B. ; Grigull, L. ; Klockgether, T. ; Spier, I. ; Heimbach, A. ; Bender, T. ; Brand, F. ; Stieber, C. ; Morawiec, A.M. ; Karakostas, P. ; Schäfer, V.S. ; Bernsen, S. ; Weydt, P. ; Castro-Gomez, S. ; Aziz, A. ; Grobe-Einsler, M. ; Kimmich, O. ; Kobeleva, X. ; Önder, D. ; Lesmann, H. ; Kumar, S. ; Tacik, P. ; Basin, M.A. ; Incardona, P. ; Lee-Kirsch, M.A. ; Berner, R. ; Schuetz, C. ; Körholz, J. ; Kretschmer, T. ; di Donato, N. ; Schröck, H. ; Heinen, A. ; Reuner, U. ; Hanßke, A.M. ; Kaiser, F.J. ; Manka, E. ; Munteanu, M. ; Kuechler, A. ; Cordula, K. ; Hirtz, R. ; Schlapakow, E. ; Schlein, C. ; Lisfeld, J. ; Kubisch, C. ; Herget, T. ; Hempel, M. ; Weiler-Normann, C. ; Ullrich, K. ; Schramm, C. ; Rudolph, C. ; Rillig, F. ; Groffmann, M. ; Muntau, A.C. ; Tibelius, A. ; Schwaibold, E.M.C. ; Schaaf, C.P. ; Zawada, M. ; Kaufmann, L. ; Hinderhofer, K. ; Okun, P.M. ; Kotzaeridou, U. ; Hoffmann, G.F. ; Choukair, D. ; Bettendorf, M. ; Spielmann, M. ; Ripke, A. ; Pauly, M. ; Munchau, A. ; Lohmann, K. ; Hüning, I. ; Hanker, B. ; Bäumer, T. ; Herzog, R. ; Hellenbroich, Y. ; Westphal, D.S. ; Strom, T. ; Kovacs, R. ; Riedhammer, K.M. ; Mayerhanser, K. ; Graf, E. ; Brugger, M. ; Hoefele, J. ; Oexle, K. ; Mirza-Schreiber, N. ; Berutti, R. ; Schatz, U. ; Krenn, M. ; Makowski, C. ; Weigand, H. ; Schröder, S. ; Rohlfs, M. ; Vill, K. ; Hauck, F. ; Borggraefe, I. ; Müller-Felber, W. ; Kurth, I. ; Elbracht, M. ; Knopp, C. ; Begemann, M. ; Kraft, F. ; Lemke, J.R. ; Hentschel, J. ; Platzer, K. ; Strehlow, V. ; Abou Jamra, R. ; Kehrer, M. ; Demidov, G. ; Beck-Wödl, S. ; Graessner, H. ; Sturm, M. ; Zeltner, L. ; Schöls, L.J. ; Magg, J. ; Bevot, A. ; Kehrer, C. ; Kaiser, N. ; Turro, E. ; Horn, D. ; Grüters-Kieslich, A. ; Klein, C. ; Mundlos, S. ; Nöthen, M. ; Riess, O. ; Meitinger, T. ; Krude, H. ; Krawitz, P.M. ; Haack, T. ; Ehmke, N. ; Wagner, M.

Next-generation phenotyping integrated in a national framework for patients with ultrarare disorders improves genetic diagnostics and yields new molecular findings.

2024 Scientific Article in Bioinformatics

Dorešić, D. ; Grein, S. ; Hasenauer, J.

Efficient parameter estimation for ODE models of cellular processes using semi-quantitative data.

Technical University of Munich

Munich Center for Machine Learning

Computational Health Center

Our Research Areas

Digital Genomics and Image Computing

Health AI

Systems Biomedicine

Discover Our Highlights

How AI is Revolutionizing Medicine

Building Reliable AI

Bavarian AI Council Meets at Helmholtz Munich

Teaching AI Psychological Skills for Better Diagnosis and Therapies

Helmholtz invests 23 million in research on AI foundation models