Dr. Marius Lange is an emerging leader in computational biology whose interdisciplinary expertise bridges physics, mathematics, and biological sciences. Since 2023, he conducts postdoctoral research at ETH Zurich (Department of Biosystems Science and Engineering), co-supervised by Barbara Treutlein (ETH Zurich) and Dana Pe’er (Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center). Originally trained in physics, Dr. Lange earned his Bachelor's degree from the University of Freiburg in Germany before advancing to the University of Oxford for his Master's in Applied Mathematics, where he developed the mathematical foundations for his future biological applications.
Dr. Lange's research has made significant contributions to the field of single-cell genomics through the development of innovative computational tools that unravel complex biological processes. During his doctoral studies at the Technical University of Munich under Professor Fabian Theis, he co-developed CellRank and moscot, two widely adopted computational frameworks that have become essential resources for biologists worldwide seeking to understand factors driving cell fate decisions in both health and disease. His current work focuses on moslin, a groundbreaking computational method that integrates lineage tracing with gene expression data to map cellular trajectories across time points, which has shown exceptional performance in analyzing C. elegans embryonic development and zebrafish heart regeneration. This tool overcomes limitations of previous approaches by simultaneously leveraging both intra-individual lineage relations and inter-individual gene expression similarity, enabling researchers to decipher complex state change trajectories from destructive single-cell experiments.
Dr. Lange's research excellence has been recognized with multiple prestigious awards, including the Helmholtz Software Award, the Rainer-Rudolph Prize, and most notably the competitive EMBO Postdoctoral Fellowship that supports his current work. His scientific approach combines rigorous mathematical frameworks with biological insight to study dynamical processes including development, regeneration, and reprogramming, with particular focus on understanding human brain development through organoid model systems. At ETH Zurich, he is developing sophisticated computational models to integrate spatio-temporal data across multiple molecular modalities, aiming to uncover the regulatory relationships that govern human development. As a passionate advocate for open science, Dr. Lange ensures all his computational tools are publicly available on GitHub, fostering collaboration and accelerating discovery across the global research community as he continues to pioneer new methodologies for understanding life's most complex biological processes.
