Malte Lücken | Helmholtz Munich

Group Leader

malte.luecken@helmholtz-munich.de Website

“I am excited to work at the intersection of the Institute for Computational Biology at the Computational Health Center and the Institute for Lung Health and Immunity at the Environmental Health Center.”

Visit Institute LHI Visit my Lab

Malte Lücken completed his foundational studies in Physics at the University of Warwick before he transitioned to working in computational biology, completing a PhD in network biology with Prof. Charlotte Deane and Prof. Gesine Reinert at the University of Oxford in the Department of Statistics in 2017. After a stint in industry, working at UCB Pharma in Belgium, he moved to Helmholtz Munich in 2018, where he first glimpsed the transformative potential of single-cell genomics during his postdoctoral research with Prof. Fabian Theis. This keen interest led him to establish his independent research group in 2022. The Luecken lab bridges the Computational Health and Environmental Health Centers, working at the interface of machine learning and single-cell genomics, with a focus on lung health.

Malte Lücken’s research focuses on three related areas of single-cell data science: systematic evaluation of tools, building cellular views of human tissues in single-cell atlases, and modelling inter-individual differences. He started in single-cell genomics by establishing the first best practice workflow for analysing single-cell data, identifying patterns in published tool benchmarks. He has since performed numerous benchmarking studies, and co-founded the Open Problems in Single-cell Analysis project, a living benchmarking framework for single-cell genomics, which he uses to run competitions to engage machine learning scientists to address unsolved challenges in single-cell data science. Leveraging these best practice pipelines, Malte Lücken integrates datasets to build cellular reference atlases of human tissues and organs, generating the first reference atlas of a human tissue in the human lung cell atlas. In this capacity, he leads the integration team of the Human Cell Atlas since 2022, a global organization of over 4000 researchers aiming to characterize the cellular landscape of healthy human tissues and organs. He combines benchmarking and atlasing expertise in developing tools to model differences between individuals. He applies these tools to identify biomarkers and build prognostic models in consortia on lung cancer, asthma, COPD, and lung transplantation.

Computational biology single-cell genomicsmachine learning data analysis benchmarking machine learning data integrationd batch correction multi-omics

Since 2024

Since 2023

Since 2022

2018 - 2022

“Deciphering the human genome allows us to sequence a person’s DNA to find regions that indicate higher disease risk. But human RNA profiles are far more diverse than DNA and can be more easily targeted by treatments. By deciphering human RNA profiles in the lung, our Human Lung Cell Atlas allows us to immediately identify cellular profiles associated with lung disease. We believe we can use this to predict disease onset, progression, and optimal treatments.”

By deciphering human RNA profiles in the lung, our Human Lung Cell Atlas allows us to immediately identify cellular profiles associated with lung disease.

Outstanding Reproducibility in Science Award for “Benchmarking atlas-level data integration in single-cell genomics”, Massive Analysis and Quality Control Society (2023)
Human Cell Atlas Integration team Chan Zuckerberg Initiative (CZI) grant (2022-2025)
Helmholtz Advance Career Fellow (2019-2020)

Li, J. ; Wang, J. ; Ibarra Del Rio, I.A. ; Cheng, X. ; Luecken, M. ; Lu, J. ; Monavarfeshani, A. ; Yan, W. ; Zheng, Y. ; Zuo, Z. ; Colborn, S.L.Z. ; Cortez, B.S. ; Owen, L.A. ; Wick, B. ; Bao, X. ; Choi, J. ; Haeussler, M. ; Tran, N.M. ; Shekhar, K. ; Sanes, J.R. ; Stout, J.T. ; Chen, S. ; Li, Y. ; DeAngelis, M.M. ; Theis, F.J. ; Chen, R.

Author Correction: Single-cell atlas of the transcriptome and chromatin accessibility in the human retina.

Li, S. ; Luecken, M. ; Marioni, J.C. ; Teichmann, S.A. ; He, P.

Toward informed batch correction for single-cell transcriptome integration.

Li, J. ; Wang, J. ; Ibarra Del Rio, I.A. ; Cheng, X. ; Luecken, M. ; Lu, J. ; Monavarfeshani, A. ; Yan, W. ; Zheng, Y. ; Zuo, Z. ; Colborn, S.L.Z. ; Cortez, B.S. ; Owen, L.A. ; Wick, B. ; Bao, X. ; Haeussler, M. ; Tran, N.M. ; Shekhar, K. ; Sanes, J.R. ; Stout, J.T. ; Chen, S. ; Li, Y. ; DeAngelis, M.M. ; Theis, F.J. ; Chen, R.

Single-cell atlas of the transcriptome and chromatin accessibility in the human retina.

De Donno, C. ; Lopez, J.P. ; Luecken, M. ; Kos, A. ; Brivio, E. ; Bordes, J. ; Yang, H. ; Deussing, J.M. ; Schmidt, M.V. ; Theis, F.J. ; Chen, A.

Single-cell characterization of the adult male hippocampus suggests a prominent, and cell-type specific, role for Nrgn and Sgk1 in response to a social stressor.

Idrees, S. ; Chen, H. ; Sadaf, T. ; Rehman, S.F. ; Johansen, M.D. ; Paudel, K.R. ; Liu, G. ; Wang, Y. ; Luecken, M. ; Hortle, E. ; Philp, A.S. ; Budden, K.F. ; O'Rourke, M. ; Kaiko, G.E. ; Lucas, S.E.M. ; Dickinson, J.L. ; Allen, P.C. ; Powell, J.E. ; Zhang, L.Y. ; Chambers, D.C. ; Corte, T. ; Caramori, G. ; Sauler, M. ; Wark, P.A. ; Gote-Schniering, J. ; Lehmann, M. ; Conlon, T.M. ; Kapellos, T. ; Yildirim, A.Ö. ; Faner, R. ; Dharmage, S.C. ; Wheelock, C.E. ; van den Berge, M. ; Nawijn, M.C. ; Polverino, F. ; Belz, G.T. ; Chotirmall, S.H. ; Segal, L.N. ; Faiz, A. ; Hansbro, P.M.

Multi-omics to study chronic respiratory diseases and viral infections.

Firsova, A.B. ; Marco Salas, S. ; Kuemmerle, L. ; Abalo, X.M. ; Sountoulidis, A. ; Larsson, L. ; Mahbubani, K.T. ; Theelke, J. ; Andrusivova, Z. ; Alonso Galicia, L. ; Liontos, A. ; Balassa, T. ; Kovács, F. ; Horvath, P. ; Chen, Y. ; Gote-Schniering, J. ; Stoleriu, M.-G. ; Behr, J. ; Meyer, K.B. ; Timens, W. ; Schiller, H.B. ; Luecken, M. ; Theis, F.J. ; Lundeberg, J. ; Nilsson, M. ; Nawijn, M.C. ; Samakovlis, C.

Spatial single-cell atlas reveals regional variations in healthy and diseased human lung.

Gerckens, M. ; Richard, A. ; Arnold, P. ; Veit, T. ; Barton, J. ; Götschke, J. ; Milger, K. ; Kauke, T. ; Schneider, C. ; Michel, S. ; Irlbeck, M. ; Luecken, M. ; Yildirim, A.O.E. ; Behr, J. ; Kneidinger, N. ; Mümmler, C.

Multistate modelling of baseline lung allograft dysfunction in lung transplant recipients.

Luecken, M. ; Gigante, S. ; Burkhardt, D.B. ; Cannoodt, R. ; Strobl, D.C. ; Markov, N.S. ; Zappia, L. ; Palla, G. ; Lewis, W. ; Dimitrov, D. ; Vinyard, M.E. ; Magruder, D.S. ; Müller, M. ; Andersson, A. ; Dann, E. ; Qin, Q. ; Otto, D.J. ; Klein, M. ; Botvinnik, O.B. ; Deconinck, L. ; Waldrant, K. ; Yasa, S.N. ; Szałata, A. ; Benz, A. ; Li, Z. ; Bloom, J.M. ; Pisco, A.O. ; Saez-Rodriguez, J. ; Wulsin, D. ; Pinello, L. ; Saeys, Y. ; Theis, F.J. ; Krishnaswamy, S.

Defining and benchmarking open problems in single-cell analysis.

Dr. Malte Lücken

On This Page

Academic Career and Research Areas

Fields of Work and Expertise

Professional Background

Chair of the steering board, DZL DataLung school

Coordinator, Artificial Intelligence and Digital Tools working group, German Center for Lung Research (DZL)

Scientific coordinator, Human Cell Atlas Integration Team

Postdoctoral researcher, Machine Learning group, Institute for Computational Biology, Helmholtz Munich, Germany

My Vision

Honors and Awards

Recent Publications

Media Coverage

"The Mapping of the Lung" - First integrated atlas of its kind for a major organ

A pioneer project at the intersection of biotechnology and artificial intelligence.

DZL DataLung School

Training the next generation of data scientists in lung research

Building a better world?

Join our team.