Results 81 to 90 of about 8,419,643 (305)

Potential therapeutic targeting of BKCa channels in glioblastoma treatment

open access: yesMolecular Oncology, EarlyView.
This review summarizes current insights into the role of BKCa and mitoBKCa channels in glioblastoma biology, their potential classification as oncochannels, and the emerging pharmacological strategies targeting these channels, emphasizing the translational challenges in developing BKCa‐directed therapies for glioblastoma treatment.
Kamila Maliszewska‐Olejniczak   +4 more
wiley   +1 more source

NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization [PDF]

open access: yesThe Web Conference, 2019
We study the problem of large-scale network embedding, which aims to learn latent representations for network mining applications. Previous research shows that 1) popular network embedding benchmarks, such as DeepWalk, are in essence implicitly ...
J. Qiu   +6 more
semanticscholar   +1 more source

Exploiting metabolic adaptations to overcome dabrafenib treatment resistance in melanoma cells

open access: yesMolecular Oncology, EarlyView.
We show that dabrafenib‐resistant melanoma cells undergo mitochondrial remodeling, leading to elevated respiration and ROS production balanced by stronger antioxidant defenses. This altered redox state promotes survival despite mitochondrial damage but renders resistant cells highly vulnerable to ROS‐inducing compounds such as PEITC, highlighting redox
Silvia Eller   +17 more
wiley   +1 more source

Neural-Brane: Neural Bayesian Personalized Ranking for Attributed Network Embedding

open access: yesData Science and Engineering, 2019
Network embedding methodologies, which learn a distributed vector representation for each vertex in a network, have attracted considerable interest in recent years.
Vachik S. Dave   +3 more
doaj   +1 more source

Attention-Aware Heterogeneous Graph Neural Network

open access: yesBig Data Mining and Analytics, 2021
As a powerful tool for elucidating the embedding representation of graph-structured data, Graph Neural Networks (GNNs), which are a series of powerful tools built on homogeneous networks, have been widely used in various data mining tasks.
Jintao Zhang, Quan Xu
doaj   +1 more source

Embedded Sensor Networks [PDF]

open access: yes, 2009
Embedded sensor networks are distributed systems for sensing and in situ processing of spatially and temporally dense data from resource-limited and harsh environments such as seismic zones, ecological contamination sites are battle fields. From an application point of view, many interesting questions arise from sensor network technology that go far ...
openaire   +1 more source

Peroxidasin enables melanoma immune escape by inhibiting natural killer cell cytotoxicity

open access: yesMolecular Oncology, EarlyView.
Peroxidasin (PXDN) is secreted by melanoma cells and binds the NK cell receptor NKG2D, thereby suppressing NK cell activation and cytotoxicity. PXDN depletion restores NKG2D signaling and enables effective NK cell–mediated melanoma killing. These findings identify PXDN as a previously unrecognized immune evasion factor and a potential target to improve
Hsu‐Min Sung   +17 more
wiley   +1 more source

VNE-AFS:virtual network embedding based on artificial fish swarm

open access: yesTongxin xuebao, 2012
Recently virtual network embedding problem had been proposed as a research challenge in the cloud computing environment.In order to reduce the costs,a virtual network embedding algorithms based on artificial fish swarm(VNE-AFS)was proposed.A binary ...
Qiang ZHU   +3 more
doaj   +2 more sources

Learning Weight Signed Network Embedding with Graph Neural Networks

open access: yesData Science and Engineering, 2023
Network embedding aims to map nodes in a network to low-dimensional vector representations. Graph neural networks (GNNs) have received much attention and have achieved state-of-the-art performance in learning node representation.
Zekun Lu   +4 more
doaj   +1 more source

Enercy Efficient Virtual Network Embedding in Data Center Optical Networks

open access: yesGuangtongxin yanjiu, 2022
To solve the energy consumption problem in Data Center Optical Networks (DCONs), an Energy Efficient Embedding algorithm based on Matching Network Resources (3E-MNR) scheme is proposed.
Jia-qi NIE
doaj   +1 more source

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