Zobrazeno 1 - 10
of 27
pro vyhledávání: '"David Schnoerr"'
Publikováno v:
PLoS Computational Biology, Vol 15, Iss 11, p e1007442 (2019)
Large-scale neural recording methods now allow us to observe large populations of identified single neurons simultaneously, opening a window into neural population dynamics in living organisms. However, distilling such large-scale recordings to build
Externí odkaz:
https://doaj.org/article/5a38f25ac88d4e268d0cc225cd8ecd8f
Publikováno v:
Nature Communications, Vol 7, Iss 1, Pp 1-11 (2016)
Stochastic reaction-diffusion systems are used for modelling spatial dynamics in many disciplines, but parameter inference and model selection remain challenging. Here the authors offer a solution enabled by a connection between reaction-diffusion an
Externí odkaz:
https://doaj.org/article/a5bdcffd971d4304ad4199e51fae2167
Publikováno v:
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Turing patterns have morphed from mathematical curiosities into highly desirable targets for synthetic biology. For a long time, their biological significance was sometimes disputed but there is now ample evidence for their involvement in processes r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4610aacdebd512f4df8ff050e9e0c088
https://doi.org/10.1098/rsta.2020.0272
https://doi.org/10.1098/rsta.2020.0272
The formation of spatial structures lies at the heart of developmental processes. However, many of the underlying gene regulatory and biochemical processes remain poorly understood. Turing patterns constitute a main candidate to explain such processe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::38148f575b3f52b5f84cef33aed6c250
https://doi.org/10.1101/2020.10.18.344135
https://doi.org/10.1101/2020.10.18.344135
Stochastic models are key to understanding the intricate dynamics of gene expression. But the simplest models which only account for e.g. active and inactive states of a gene fail to capture common observations in both prokaryotic and eukaryotic orga
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d944c7439c5be667a916ff43afb2582
https://doi.org/10.1101/2020.01.05.895359
https://doi.org/10.1101/2020.01.05.895359
Publikováno v:
Journal of Theoretical Biology. 531:110901
The formation of spatial structures lies at the heart of developmental processes. However, many of the underlying gene regulatory and biochemical processes remain poorly understood. Turing patterns constitute a main candidate to explain such processe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ccd1da80f0fd02f35745ec547fbfb7fc
https://doi.org/10.1016/j.jtbi.2021.110901
https://doi.org/10.1016/j.jtbi.2021.110901
Publikováno v:
257.e4
Summary Turing patterns (TPs) underlie many fundamental developmental processes, but they operate over narrow parameter ranges, raising the conundrum of how evolution can ever discover them. Here we explore TP design space to address this question an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::45627a7504c07fa41eceb605291e4d1a
http://hdl.handle.net/10044/1/70533
http://hdl.handle.net/10044/1/70533
Publikováno v:
Journal of mathematical biology. 80(6)
It is well known that stochastically modeled reaction networks that are complex balanced admit a stationary distribution that is a product of Poisson distributions. In this paper, we consider the following related question: supposing that the initial
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dc90cb8e28f51e6c0a6593a4710e461d
https://pubmed.ncbi.nlm.nih.gov/32211950
https://pubmed.ncbi.nlm.nih.gov/32211950
Turing patterns (TPs) underlie many fundamental developmental processes, but they operate over narrow parameter ranges, raising the conundrum of how evolution can ever discover them. Here we explore TP design space to address this question and to dis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::600335b858fbc499bb04050b532df18e
Publikováno v:
Quantitative Evaluation of Systems ISBN: 9783319991535
QEST
QEST
Probabilistic model checking for systems with large or unbounded state space is a challenging computational problem in formal modelling and its applications. Numerical algorithms require an explicit representation of the state space, while statistica
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0b673a34fbb0ffc72e1d832898f5a3da
https://doi.org/10.1007/978-3-319-99154-2_18
https://doi.org/10.1007/978-3-319-99154-2_18