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Activity motifs reveal principles of timing in transcriptional control of the yeast metabolic network

, , , , , and . Nat. Biotechnol., (2008)

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The pi-calculus as an abstraction for biomolecular systems, and . (2004)Inferring quantitative models of regulatory networks from expression data., , and . ISMB/ECCB (Supplement of Bioinformatics), page 248-256. (2004)Representation and Simulation of Biochemical Processes Using the pi-Calculus Process Algebra., , and . Pacific Symposium on Biocomputing, page 459-470. (2001)A functional selection model explains evolutionary robustness despite plasticity in regulatory networks, , , , and . Molecular Systems Biology, 8 (1): n/a (Oct 23, 2012)Reconstructing probabilistic trees of cellular differentiation from single-cell RNA-seq data., , , , , , and . CoRR, (2018)Disentangling shared and group-specific variations in single-cell transcriptomics data with multiGroupVI., , , and . MLCB, volume 200 of Proceedings of Machine Learning Research, page 16-32. PMLR, (2022)Impulse Control: Temporal Dynamics in Gene Transcription, and . Cell, 144 (6): 886 - 896 (2011)Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling., , , , , and . CLeaR, volume 213 of Proceedings of Machine Learning Research, page 662-691. PMLR, (2023)Minreg: Inferring an active regulator set., , and . ISMB, page 258-267. (2002)Learning Module Networks, , , , and . CoRR, (2012)