斜
发表于 2025-3-23 11:19:26
A Kinetic Model of Sorting that Predicts Ligand Effects, sorting. Although this mechanism is successful in explaining the kinetics and efficiency of receptor recycling in many systems, the mechanism allowed for variations in the sorting outcome only as a result of variations in the values of the vesicle radius R, the tubule radius b, the distribution of
轻推
发表于 2025-3-23 16:06:38
Conclusions, targets molecules to their final destinations. By controlling the fraction of internalized receptors that recycle to the cell surface, the cell can regulate its ability to bind extracellular ligand and can thus modulate its response to a particular ligand. Similarly, a cell may choose to degrade li
缝纫
发表于 2025-3-23 21:32:27
A Kinetic Model of Sorting that Predicts Ligand Effects, for variations in the sorting outcome only as a result of variations in the values of the vesicle radius R, the tubule radius b, the distribution of volume between the endosome vesicle and tubules, the diffusion coefficient of the receptor D., the dimensionless current β, the partition coefficient κ, and the sorting time τ*.
Biomarker
发表于 2025-3-24 00:49:24
Jennifer J. Linderman,Douglas A. Lauffenburgereveloped; it recommends stocks that fit the strategy of investors, and its recommendations are explainable for investment advisers..978-3-030-75523-2978-3-030-75521-8Series ISSN 1860-949X Series E-ISSN 1860-9503
护航舰
发表于 2025-3-24 05:03:41
Jennifer J. Linderman,Douglas A. Lauffenburgereveloped; it recommends stocks that fit the strategy of investors, and its recommendations are explainable for investment advisers..978-3-030-75523-2978-3-030-75521-8Series ISSN 1860-949X Series E-ISSN 1860-9503
Crayon
发表于 2025-3-24 10:08:38
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babble
发表于 2025-3-24 12:28:26
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Extemporize
发表于 2025-3-24 18:01:12
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浮雕
发表于 2025-3-24 18:59:55
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明智的人
发表于 2025-3-25 01:43:12
Jennifer J. Linderman,Douglas A. Lauffenburger is proposed for predicting misinformation spread by leveraging GraphSAGE with heterogeneous graph convolution. Secondly, we propose an explanation module that uses gradient-based and perturbation-based methods, to identify what makes misinformation spread by explaining the trained prediction module