Cell-signalling dynamics in time and space

By Boris N. Kholodenko. Nature reviews. Molecular cell biology, 2006

1,380 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/5e94e12aae1769fa195dc5bbe54b3d6a5afe4916

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Citations in the corpus

Feedback regulation of EGFR signalling: decision making by early and delayed loops (2011, background): “By increasing the number of possible protein interactions, the layered network allows signal specificity and diverse biological outcome”
Growth factor-induced MAPK network topology shapes Erk response determining PC-12 cell fate (2007, background): “As hysteresis, to the point of irreversibility, is a hallmark of bistabilit”
Computer Methods and Programs in Biomedicine (2019, background): “Hence, the knowledge of the connections within a neuronal network and its spatiotemporal properties can provide an insight into gene activation patterns, physiological responses, and pivotal cellular decisions [4] .”
Rule-based modeling of biochemical systems with BioNetGen. (2009, background): “These transformations are (1) add a bond, ( 2 ) delete a bond, (3) change a component state label, (4) delete a molecule, or (5) add a molecule.”
Riding the DUBway: regulation of protein trafficking by deubiquitylating enzymes (2006, neutral): “For instance, peroxiredoxin II, through its association with PDGFR, suppresses PDGF signaling, whereas the less targeted catalase and glutathione peroxidase have no effect (Choi et al., 2005).”
The MEK/ERK cascade: from signaling specificity to diverse functions. (2007, background): “In addition, scaffold proteins can provide better stability to some of the cascade components, to determine the threshold of signaling and lead to different functions of a given cascade by recruiting of different substrates to individual cascade components [87,107,108].”
Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review (2012, background): “iation mechanisms, such as scaffolding proteins, crosspathway inhibitions, kinetic insulation, and the spatial and temporal expression patterns of proteins (Freeman, 2000; Bhattacharyya et al., 2006; Kholodenko, 2006; Behar et al., 2007; Haney et al., 2010; Lewitzky et al., 2012). The regulatory sub”
Utilizing graph machine learning within drug discovery and development (2021, positive): “mRNA and proteins exhibit stochastic dynamics [231, 232].”
Signalling ballet in space and time (2010, positive): “Transcriptional negative feedback generated by ERK-mediated DUSP expression can bring about ERK and DUSP oscillations that develop on a longer timescale than oscillations arising from immediate negative feedback in the cytoso”
Causal network inference using biochemical kinetics (2014, positive): “Phosphorylation kinetics have been widely studied (Kholodenko, 2006), and ODE formulations are available, including those based on Michaelis–Menten kinetics (Leskovac, 2003).”
EGF–ERBB signalling: towards the systems level (2006, methodology): “In silico replicas of cellular networks are therefore becoming an increasingly useful tool for network descriptio”
Systems biology and combination therapy in the quest for clinical efficacy (2006, background): “However, large models with multiple signaling circuits raise new conceptual issues, such as how best to represent the partitioning of shared components (for example, Ras, MAP kinases and others) among potentially competing pathway”
The lipid kinase PI5P4Kβ is an intracellular GTP sensor for metabolism and tumorigenesis (2016, neutral): “In support of this notion, many biological systems are not linear and signaling activities are dynamically propagated in a spatiotemporal manner through feedback amplification and site-specific localization (Kholodenko, 2006).”
Network inference using steady-state data and Goldbeter-Koshland kinetics (2012, methodology): “Following the biochemical literature (Kholodenko, 2006; Steijaert et al., 2010), we use ODEs of the Michaelis-Menten type to provide a suitable class of analytic approximations for phosphorylation dynamics.”