Results 61 to 70 of about 184,942 (303)
Tau acetylation at K331 has limited impact on tau pathology in vivo
FEBS Letters, EarlyView.We mapped tau post‐translational modifications in humanized MAPT knock‐in mice and in amyloid‐bearing double knock‐in mice. Acetylation within the repeat domain, particularly around K331, showed modest increases under amyloid pathology. To test functional relevance, we generated MAPTK331Q knock‐in mice.
Shoko Hashimoto +3 more
wiley +1 more source
Hyperosmotic stress induces PARP1‐mediated HPF1‐dependent mono(ADP‐ribosyl)ation
FEBS Letters, EarlyView.Sorbitol‐induced hyperosmotic stress rapidly induces reversible mono(ADP‐ribosyl)ation (MARylation) on PARP1 without the signs of genotoxic signaling. We show that PARP1 autoMARylation is HPF1 dependent and forms hydroxylamine‐resistant O‐glycosidic linkages.
Anna Georgina Kopasz +11 more
wiley +1 more source
Selective sampling on graphs for classification [PDF]
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, 2013 Selective sampling is an active variant of online learning in which the learner is allowed to adaptively query the label of an observed example. The goal of selective sampling is to achieve a good trade-off between prediction performance and the number of queried labels. Existing selective sampling algorithms are designed for vector-based data. In this
Quanquan Gu +3 more
openaire +1 more source
An isoform of 14‐3‐3 protein regulates transbilayer lipid movement at the plasma membrane
FEBS Letters, EarlyView.Loss of 14‐3‐3ζ in CHO cells confers resistance to exogenous phosphatidylserine (PS) and impairs endocytosis‐independent inward flip‐flop of fluorescent PS at the plasma membrane. RNAi‐mediated knockdown reproduces this defect, while no additive effect is seen in ATP11C‐deficient cells.
Akiko Yamaji‐Hasegawa +3 more
wiley +1 more source
SamGoG: A Sampling-Based Graph-of-Graphs Framework for Imbalanced Graph Classification
CoRRGraph Neural Networks (GNNs) have shown remarkable success in graph classification tasks by capturing both structural and feature-based representations. However, real-world graphs often exhibit two critical forms of imbalance: class imbalance and graph size imbalance.
Shangyou Wang, Zezhong Ding, Xike Xie
openaire +2 more sources
Biophysical approaches for studying viral entry
FEBS Letters, EarlyView.Viruses infect all living organisms and have been responsible for major epidemics and pandemics. Their ongoing evolutionary battle with host defenses creates a constant need for improved tools to study viral behavior. Advancing methods to probe viral attachment, fusion, and genome release deepen our understanding of how infections begin and support the
Inbar Yosibash, Raya Sorkin
wiley +1 more source
Improved Graph Neural Networks for Spatial Networks Using Structure-Aware Sampling
ISPRS International Journal of Geo-Information, 2020 Graph Neural Networks (GNNs) have received wide acclaim in recent times due to their performance on inference tasks for unstructured data. Typically, GNNs operate by exploiting local structural information in graphs and disregarding their global ...
Chidubem Iddianozie, Gavin McArdle
doaj +1 more source
FEBS Letters, EarlyView.Septin 9 polybasic domains couple phosphoinositide‐rich membrane binding to centrosome positioning, Golgi organization, and microtubule acetylation to control epithelial polarity. Their loss disrupts this axis, causing centrosome mispositioning, Golgi fragmentation, reduced microtubule acetylation, and polarity inversion via upregulation of the ...
Ting ting Cai +4 more
wiley +1 more source
, 2011 Randomized graph sampling (RGS) is an approach for sampling populations associated with or describable as graphs, when the structure of the graph is known and the parameter of interest is the total weight of the graph.
Ducey, Mark J., Mark J. Ducey
core +1 more source
On sampling from massive graph streams [PDF]
, 2017 We propose Graph Priority Sampling ( gps ), a new paradigm for order-based reservoir sampling from massive graph streams.
Nesreen K. Ahmed +3 more
core +1 more source