2022
DOI: 10.1007/978-1-0716-2172-1_36
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Formalizing Phenotypes of Regeneration

Abstract: Regeneration experiments can produce complex phenotypes including morphological outcomes and gene expression patterns that are crucial for the understanding of the mechanisms of regeneration. However, due to their inherent complexity, variability between individuals, and heterogeneous data spreading across the literature, extracting mechanistic knowledge from them is a current challenge. Toward this goal, here we present protocols to unambiguously formalize the phenotypes of regeneration and their experimental… Show more

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Cited by 3 publications
(1 citation statement)
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“…Indeed, it is a current challenge to produce mechanistic hypotheses in terms of GRMs that can recapitulate observed spatial phenotypes. The methodology presented here could be employed to automatically infer such hypotheses directly from datasets of curated experimental gene expression patterns (Lobo, 2022;Roy et al, 2020). Overall, the presented method to aid in the design of GRMs able to produce arbitrary gene expression patterns has the potential to both enable the understanding of complex developmental processes as well as the design of complex dynamic synthetic systems.…”
Section: Designing Grms For Arbitrary Shapesmentioning
confidence: 99%
“…Indeed, it is a current challenge to produce mechanistic hypotheses in terms of GRMs that can recapitulate observed spatial phenotypes. The methodology presented here could be employed to automatically infer such hypotheses directly from datasets of curated experimental gene expression patterns (Lobo, 2022;Roy et al, 2020). Overall, the presented method to aid in the design of GRMs able to produce arbitrary gene expression patterns has the potential to both enable the understanding of complex developmental processes as well as the design of complex dynamic synthetic systems.…”
Section: Designing Grms For Arbitrary Shapesmentioning
confidence: 99%