Huang, Y.* ; Urban, C.* ; Hubel, P.* ; Stukalov, A.* ; Pichlmair, A.
Protein turnover regulation is critical for influenza A virus infection.
Cell Syst. 15, 911-929 (2024)
Ntini, E.* ; Budach, S.* ; Vang Ørom, U.A.* ; Marsico, A.
Genome-wide measurement of RNA dissociation from chromatin classifies transcripts by their dynamics and reveals rapid dissociation of enhancer lncRNAs.
Cell Syst. 14, 906-922.e6 (2023)
Theis, F.J. ; Dar, D.* ; Vento-Tormo, R.* ; Vicković, S.* ; Wang, L.* ; Kagohara, L.T.* ; Rendeiro, A.F.* ; Joyce, J.A.*
What do you most hope spatial molecular profiling will help us understand? Part 1.
Cell Syst. 14, 423-427 (2023)
Boe, R.H.* ; Ayyappan, V.* ; Schuh, L. ; Raj, A.*
Allelic correlation is a marker of trade-offs between barriers to transmission of expression variability and signal responsiveness in genetic networks.
Cell Syst. 13, 1016-1032.e6 (2022)
Aliee, H. ; Theis, F.J.
AutoGeneS: Automatic gene selection using multi-objective optimization for RNA-seq deconvolution.
Cell Syst. 12, 706-715.e4 (2021)
Ji, Y. ; Lotfollahi, M. ; Wolf, F.A. ; Theis, F.J.
Machine learning for perturbational single-cell omics.
Cell Syst. 12, 522-537 (2021)
Schuh, L. ; Loos, C. ; Pokrovsky, D.* ; Imhof, A.* ; Rupp, R.A.W.* ; Marr, C.
H4K20 methylation is differently regulated by dilution and demethylation in proliferating and cell-cycle-arrested xenopus embryos.
Cell Syst. 11, 653-662.e8 (2020)
Schuh, L. ; Saint-Antoine, M.* ; Sanford, E.M.* ; Emert, B.L.* ; Singh, A.* ; Marr, C. ; Raj, A.* ; Goyal, Y.*
Gene networks with transcriptional bursting recapitulate rare transient coordinated high expression states in cancer.
Cell Syst. 10, 363-378.e12 (2020)
Fröhlich, F. ; Kessler, T.* ; Weindl, D. ; Shadrin, A.* ; Schmiester, L. ; Hache, H.* ; Muradyan, A.* ; Schütte, M.* ; Lim, J.H.* ; Heinig, M. ; Theis, F.J. ; Lehrach, H.* ; Wierling, C.* ; Lange, B.* ; Hasenauer, J.
Efficient parameter estimation enables the prediction of drug response using a mechanistic pan-cancer pathway model.
Cell Syst. 7, 567-579 (2018)
Loos, C. ; Möller, K.* ; Fröhlich, F. ; Hucho, T.* ; Hasenauer, J.
A hierarchical, data-driven approach to modeling single-cell populations predicts latent causes of cell-to-cell variability.
Cell Syst. 6, 593-603.e13 (2018)
Martinez-Corral, R.* ; Raimundez-Alvarez, E. ; Lin, Y.* ; Elowitz, M.B.* ; Garcia-Ojalvo, J.*
Self-amplifying pulsatile protein dynamics without positive feedback.
Cell Syst. 7, 453-462 (2018)
Jagiella, N. ; Rickert, D. ; Theis, F.J. ; Hasenauer, J.
Parallelization and high-performance computing enables automated statistical inference of multi-scale models.
Cell Syst. 4, 194–206.e9 (2017)
Blasi, T. ; Feller, C.* ; Feigelman, J. ; Hasenauer, J. ; Imhof, A.* ; Theis, F.J. ; Becker, P.B.* ; Marr, C.
Combinatorial histone acetylation patterns are generated by motif-specific reactions.
Cell Syst. 2, 49-58 (2016)
Carpenter, A.* ; Eddy, S.E.* ; Flicek, P.* ; Gymrek, M.* ; Hammell, M.* ; Jaqaman, K.* ; Jenkins, J.* ; Koller, D.* ; Lappalainen, T.* ; Oshlack, A.* ; Shamir, R.* ; Singh, M.* ; Teichmann, S.* ; Theis, F.J. ; Troyanskaya, O.*
What is the key best practice for collaborating with a computational biologist?
Cell Syst. 3, 7-11 (2016)
Feigelman, J. ; Ganscha, S. ; Hastreiter, S.* ; Schwarzfischer, M. ; Filipczyk, A.* ; Schröder, T.* ; Theis, F.J. ; Marr, C. ; Claassen, M.
Analysis of cell lineage trees by exact bayesian inference identifies negative autoregulation of nanog in mouse embryonic stem cells.
Cell Syst. 3, 480-490 (2016)