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