Theis Lab
ML in Single-Cell Genomics
Our research explores a broad range of machine learning (ML) approaches in computational biology, with a particular emphasis on single-cell analysis. We develop state-of-the-art algorithms to solve challenging biological questions and to accelerate medical discovery.
Our research explores a broad range of machine learning (ML) approaches in computational biology, with a particular emphasis on single-cell analysis. We develop state-of-the-art algorithms to solve challenging biological questions and to accelerate medical discovery.
Our team
Postdoc
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Software engineer
Software engineer
Software engineer
Software engineer
PhD candidate
PhD candidate
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PhD candidate
PhD candidate
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PhD candidate
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Research assistant
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Visiting researcher
Publications
Palma, A. ; Rybakov, S. ; Hetzel, L. ; Günnemann, S. ; Theis, F.J.
Enforcing Latent Euclidean Geometry in Single-Cell VAEs for Manifold Interpolation.Türei, D. ; Schaul, J. ; Palacio-Escat, N. ; Bohár, B. ; Bai, Y. ; Ceccarelli, F. ; Çevrim, E. ; Daley, M. ; Darcan, M. ; Dimitrov, D. ; Dogan, T. ; Domingo-Fernández, D. ; Dugourd, A. ; Gábor, A. ; Gul, L. ; Hall, B.A. ; Hoyt, C.T. ; Ivanova, O. ; Klein, M. ; Lawrence, T. ; Mañanes, D. ; Módos, D. ; Müller-Dott, S. ; Ölbei, M. ; Schmidt, C. ; Şen, B. ; Theis, F.J. ; Ünlü, A. ; Ulusoy, E. ; Valdeolivas, A. ; Korcsmáros, T. ; Saez-Rodriguez, J.
OmniPath: Integrated knowledgebase for multi-omics analysis.Lucarelli, D. ; Kos, T. ; Shull, C. ; Jimenez, S. ; Öllinger, R. ; Rad, R. ; Saur, D. ; Theis, F.J.
QuiCAT: A scalable and flexible framework for mapping synthetic sequences.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.Boerstler, T. ; Kachkin, D. ; Gerasimova, E. ; Zagha, N. ; Furlanetto, F. ; Nayebzade, N. ; Zappia, L. ; Boisvert, M. ; Farrell, M. ; Ploetz, S. ; Prots, I. ; Regensburger, M. ; Günther, C. ; Winkler, J. ; Gupta, P. ; Theis, F.J. ; Karow, M. ; Falk, S. ; Winner, B. ; Krach, F.
Deciphering brain organoid heterogeneity by identifying key quality determinants.Voss, C. ; Han, L. ; Ansari, M. ; Strunz, M. ; Haefner, V. ; Angelidis, I. ; Mayr, C.H. ; Berthing, T. ; Zhou, Q. ; Günther, E. ; Huzain, O. ; Schmid, O. ; Vogel, U. ; Schniering, J. ; Gaedcke, S. ; Theis, F.J. ; Schiller, H.B. ; Stöger, T.
Toward a ToxAtlas of carbon-based nanomaterials: Single-cell RNA sequencing reveals initiating cell circuits in pulmonary inflammation.Hrovatin, K. ; Moinfar, A.A. ; Zappia, L. ; Parikh, S. ; Tejada Lapuerta, A. ; Lengerich, B. ; Kellis, M. ; Theis, F.J.
Integrating single-cell RNA-seq datasets with substantial batch effects.Tejada Lapuerta, A. ; Schaar, A. ; Gutgesell, R.M. ; Palla, G. ; Halle, L. ; Minaeva, M. ; Vornholz, L. ; Dony, L. ; Drummer, F. ; Richter, T. ; Bahrami, M. ; Theis, F.J.
Nicheformer: A foundation model for single-cell and spatial omics.DeMeo, B. ; Nesbitt, C. ; Miller, S.A. ; Burkhardt, D.B. ; Lipchina, I. ; Fu, D. ; Holderreith, P. ; Kim, D. ; Kolchenko, S. ; Szalata, A. ; Gupta, I. ; Kerr, C. ; Pfefer, T.J. ; Rojas-Rodriguez, R. ; Kuppassani, S. ; Kruidenier, L. ; Doshi, P.B. ; Zamanighomi, M. ; Collins, J.J. ; Shalek, A.K. ; Theis, F.J. ; Cortes, M.
Active learning framework leveraging transcriptomics identifies modulators of disease phenotypes.Yang, K. ; Spitzer, H. ; Sterr, M. ; Hrovatin, K. ; de la O, S. ; Zhang, X. ; Setyono, E.S.A. ; Ud-Dean, M. ; Walzthoeni, T. ; Flisikowski, K. ; Flisikowska, T. ; Schnieke, A. ; Scheibner, K. ; Wells, J.M. ; Sneddon, J.B. ; Kessler, B. ; Wolf, E. ; Kemter, E. ; Theis, F.J. ; Lickert, H.
A multimodal cross-species comparison of pancreas development.