Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Gard Spreemann"'
Autor:
Patrick A. Sandoz, Robin A. Denhardt-Eriksson, Laurence Abrami, Luciano A. Abriata, Gard Spreemann, Catherine Maclachlan, Sylvia Ho, Béatrice Kunz, Kathryn Hess, Graham Knott, Francisco S. Mesquita, Vassily Hatzimanikatis, F. Gisou van der Goot
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-17 (2023)
A key player in the formation of endoplasmic reticulum sheets is CLIMP-63, but mechanistic details remained elusive. Here authors combined cellular experiments and mathematical modelling to show that S-acylation of CLIMP-63 regulates its function by
Externí odkaz:
https://doaj.org/article/e2c0d4d357a547d2987d3099985f5053
Autor:
Wei Jiao, Gard Spreemann, Evelyne Ruchti, Soumya Banerjee, Samuel Vernon, Ying Shi, R Steven Stowers, Kathryn Hess, Brian D McCabe
Publikováno v:
eLife, Vol 11 (2022)
Establishing with precision the quantity and identity of the cell types of the brain is a prerequisite for a detailed compendium of gene and protein expression in the central nervous system (CNS). Currently, however, strict quantitation of cell numbe
Externí odkaz:
https://doaj.org/article/78434984d9064053918b2af6e72da401
Publikováno v:
Network Neuroscience, Vol 3, Iss 3, Pp 725-743 (2019)
One of the paramount challenges in neuroscience is to understand the dynamics of individual neurons and how they give rise to network dynamics when interconnected. Historically, researchers have resorted to graph theory, statistics, and statistical m
Externí odkaz:
https://doaj.org/article/4083448ecd894a3ba0ea916a00eff579
The growing complexity and capacity demands for mobile networks necessitate innovative techniques for optimizing resource usage. Meanwhile, recent breakthroughs have brought Reinforcement Learning (RL) into the domain of continuous control of real-wo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::84465157ea3b9d6c271a0d973e0d65a9
http://arxiv.org/abs/2209.13540
http://arxiv.org/abs/2209.13540
Autor:
Patrick Sandoz, Robin Denhardt-Eriksson, Laurence Abrami, Luciano Abriata, Gard Spreemann, Catherine Maclachlan, Sylvia Ho, Béatrice Kunz, Kathryn Hess, Graham Knott, Francisco Mesquita, Vassily Hatzimanikatis, F. van der Goot
The complex architecture of the endoplasmic reticulum (ER) comprises distinct dynamic features, many at the nanoscale, that enable the coexistence of the nuclear envelope, regions of dense sheets and a branched tubular network that spans the cytoplas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ee5a4253516c7703b085e3f8c5cb7ac4
https://doi.org/10.21203/rs.3.rs-1373493/v1
https://doi.org/10.21203/rs.3.rs-1373493/v1
Autor:
Wei, Jiao, Gard, Spreemann, Evelyne, Ruchti, Soumya, Banerjee, Samuel, Vernon, Ying, Shi, R Steven, Stowers, Kathryn, Hess, Brian D, McCabe
Publikováno v:
eLife. 11
Establishing with precision the quantity and identity of the cell types of the brain is a prerequisite for a detailed compendium of gene and protein expression in the central nervous system (CNS). Currently, however, strict quantitation of cell numbe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::df5d071c4c4aa497c5da089602368b0d
https://pubmed.ncbi.nlm.nih.gov/35801638
https://pubmed.ncbi.nlm.nih.gov/35801638
Poster presented at the workshop Geometry of Complex Web (Les Diablaretes, February 2-5 2020 https://sites.google.com/view/geocow2020).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::27f9869a76cb4eceba601a714ead18f1
Autor:
Katharine Turner, Gard Spreemann
Publikováno v:
Topological Data Analysis ISBN: 9783030434076
Persistent homology allows us to create topological summaries of complex data. In order to analyse these statistically, we need to choose a topological summary and a relevant metric space in which this topological summary exists. While different summ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fe9c302428638dbd8b14fe70a822d653
https://doi.org/10.1007/978-3-030-43408-3_18
https://doi.org/10.1007/978-3-030-43408-3_18
Autor:
Stefania Ebli, Gard Spreemann
Publikováno v:
ICMLA
We outline a novel clustering scheme for simplicial complexes that produces clusters of simplices in a way that is sensitive to the homology of the complex. The method is inspired by, and can be seen as a higher-dimensional version of, graph spectral
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f27e7b496d248990f37a31e4acf1286
http://arxiv.org/abs/1910.07247
http://arxiv.org/abs/1910.07247