Cell‐cycle regulation of NOTCH signaling during
            <i>C. elegans</i>
            vulval development

Nusser-Stein, Stefanie; Beyer, Antje; Rimann, Ivo; Adamczyk, Magdalene; Piterman, Nir; Hajnal, Alex; Fisher, Jasmin

doi:10.1038/msb.2012.51

Cited by 42 publications

(48 citation statements)

References 68 publications

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“…By utilizing a NICD::GFP reporter, it was demonstrated that CYE-1 exerts a stabilizing effect on the intercellular pool of NICD in VPCs. 47 It is enticing to surmise that CYE-1 may exert a similar stabilizing effect on GLP-1 ICD in the germline mitotic zone. If this indeed is the case, then Cyclin E would maintain the proliferative mode of mitotic germ cells by both positively stabilizing the GLP-1/Notch proliferative cue and negatively targeting GLD-1 to prevent the transition to meiosis (Fig.…”

Section: The Role Of Cyclin E In Regulating the Transition From Germ mentioning

confidence: 99%

Divide and differentiate

et al. 2014

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Section: The Role Of Cyclin E In Regulating the Transition From Germ mentioning

confidence: 99%

Divide and differentiate

et al. 2014

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“…The development of the vulva from a row of six cells is a paradigm for understanding organogenesis, and has been modelled previously, using executable [7][8][9]28], mathematical [29,30] and hybrid models [31]. We initially validate our approach by comparing our models' ability to accurately reproduce the behaviours of previous formal models.…”

Section: Introductionmentioning

confidence: 99%

“…This patterning is invariant in wild-type animals, and can be disrupted by mutations in different parts of the pathways. Previously, a diagrammatic model proposed by Sternberg & Horvitz [8,16] was formalized and refined to describe independent cellular timings and a wide range of different observed mutations [7,9]. A key finding here was the role of bounded asynchrony in the development of cell fates [9,17], leading to multiple possible cell fate patterns when the gene lin-15 is mutated.…”

Section: Introductionmentioning

confidence: 99%

“…Previously, a diagrammatic model proposed by Sternberg & Horvitz [8,16] was formalized and refined to describe independent cellular timings and a wide range of different observed mutations [7,9]. A key finding here was the role of bounded asynchrony in the development of cell fates [9,17], leading to multiple possible cell fate patterns when the gene lin-15 is mutated. Bounded asynchrony allows cells to progress semi-independently; this allows individual cells to develop at differing rates, but ensures that the degree of variation is limited by forcing fast developing cells to wait for their neighbours.…”

Section: Introductionmentioning

confidence: 99%

“…State-based approaches specifically have been successfully applied to model a wide range of biological systems, including pancreatic organogenesis [4], T-cell differentiation [5,6], vulval development [7][8][9] and gene regulatory networks [10,11]. One of the advantages of these approaches is their ability to prove a given result.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Logic programming to predict cell fate patterns and retrodict genotypes in organogenesis

Hall

Jackson

Hajnal

et al. 2014

J. R. Soc. Interface.

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Caenorhabditis elegans vulval development is a paradigm system for understanding cell differentiation in the process of organogenesis. Through temporal and spatial controls, the fate pattern of six cells is determined by the competition of the LET-23 and the Notch signalling pathways. Modelling cell fate determination in vulval development using state-based models, coupled with formal analysis techniques, has been established as a powerful approach in predicting the outcome of combinations of mutations. However, computing the outcomes of complex and highly concurrent models can become prohibitive. Here, we show how logic programs derived from state machines describing the differentiation of C. elegans vulval precursor cells can increase the speed of prediction by four orders of magnitude relative to previous approaches. Moreover, this increase in speed allows us to infer, or 'retrodict', compatible genomes from cell fate patterns. We exploit this technique to predict highly variable cell fate patterns resulting from dig-1 reduced-function mutations and let-23 mosaics. In addition to the new insights offered, we propose our technique as a platform for aiding the design and analysis of experimental data.

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Constructing and Analyzing Computational Models of Cell Signaling with BioModelAnalyzer

Hall

Fisher

2020

CP in Bioinformatics

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BioModelAnalyzer (BMA) is an open‐source graphical tool for the development of executable models of protein and gene networks within cells. Based upon the Qualitative Networks formalism, the user can rapidly construct large networks, either manually or by connecting motifs selected from a built‐in library. After the appropriate functions for each variable are defined, the user has access to three analysis engines to test the model. In addition to standard simulation tools, BMA includes an interface to the stability‐testing algorithm and to a graphical Linear Temporal Logic (LTL) editor and analysis tool. Alongside this, we have developed a novel ChatBot to aid users constructing LTL queries and to explain the interface and run through tutorials. Here we present worked examples of model construction and testing via the interface. As an initial example, we discuss fate decisions in Dictyostelium discoidum and cAMP signaling. We go on to describe the workflow leading to the construction of a published model of the germline of C. elegans. Finally, we demonstrate how to construct simple models from the built‐in network motif library. © 2020 by John Wiley & Sons, Inc. Basic Protocol 1: Modeling the signaling network of Dictyostelium discoidum Basic Protocol 2: Modeling the germline progression of Caenorhabditis elegans Basic Protocol 3: Constructing a model of the cell cycle using motifs

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Cell‐cycle regulation of NOTCH signaling during C. elegans vulval development

Abstract: Through an iterative process of computational modeling, prediction, and experimentation, a molecular synchronization mechanism is revealed by which the cell-cycle regulates Notch signaling to allow the formation of a stable cell fate pattern.

Cited by 42 publications

References 68 publications

Divide and differentiate

Divide and differentiate

Logic programming to predict cell fate patterns and retrodict genotypes in organogenesis

Constructing and Analyzing Computational Models of Cell Signaling with BioModelAnalyzer

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