Results 91 to 100 of about 1,932,979 (312)

Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning

Nature Communications, 2019
Computational modeling of chemical and biological systems at atomic resolution is a crucial tool in the chemist’s toolset. The use of computer simulations requires a balance between cost and accuracy: quantum-mechanical methods provide high accuracy but ...
Justin S. Smith, B. Nebgen, R. Zubatyuk, N. Lubbers, Christian Devereux, K. Barros, S. Tretiak, O. Isayev, A. Roitberg   +8 more
semanticscholar   +1 more source

Self-Organization of Topographic Mixture Networks Using Attentional Feedback [PDF]

, 1999
This paper proposes a biologically-motivated neural network model of supervised learning. The model possesses two novel learning mechanisms. The first is a network for learning topographic mixtures.
Williamson, James R.
core   +1 more source

A Digital Neuromorphic Architecture Efficiently Facilitating Complex Synaptic Response Functions Applied to Liquid State Machines

, 2017
Information in neural networks is represented as weighted connections, or synapses, between neurons. This poses a problem as the primary computational bottleneck for neural networks is the vector-matrix multiply when inputs are multiplied by the neural ...
Aimone, James B., Carlson, Kristofor D., Donaldson, Jonathon, Follett, David R., Follett, Pamela L., Hill, Aaron J., James, Conrad D., Naegle, John H., Smith, Michael R., Vineyard, Craig M.   +9 more
core   +1 more source

Transcriptional regulation of neuropeptide receptors underlies context‐dependent adaptation in Drosophila melanogaster

FEBS Open Bio, EarlyView.
Under environmental changes, the expression level of neuropeptide (NP) and neuropeptide receptor (NPR) genes changes to confer context‐dependent adaptation to the model organism Drosophila melanogaster. Through finding more regulatory elements in the NPR genes in comparison with their ligands (NPs), we found that NPR‐biased transcriptional regulation ...
SeungHeui Ryu, Yanan Wei, Zekun Wu, Tianmu Zhang, DoHoon Lee, Hadi Najafi, Woo Jae Kim   +6 more
wiley   +1 more source

Building an artificial neural network with neurons

AIP Advances, 2019
Artificial neural networks are based on mathematical models of biological networks, but it is not clear how similar these two networks are. We have recently demonstrated that we can mechanically manipulate single neurons and create functioning synapses ...
M. Rigby, M. Anthonisen, X. Y. Chua, A. Kaplan, A. E. Fournier, P. Grütter   +5 more
doaj   +1 more source

Topological Properties of Neuromorphic Nanowire Networks

Frontiers in Neuroscience, 2020
Graph theory has been extensively applied to the topological mapping of complex networks, ranging from social networks to biological systems. Graph theory has increasingly been applied to neuroscience as a method to explore the fundamental structural and
Alon Loeffler, Ruomin Zhu, Joel Hochstetter, Mike Li, Kaiwei Fu, Adrian Diaz-Alvarez, Tomonobu Nakayama, James M. Shine, Zdenka Kuncic   +8 more
doaj   +1 more source

Backpropagation Artificial Neural Network To Detect Hyperthermic Seizures In Rats [PDF]

, 2002
A three-layered feed-forward back-propagation Artificial Neural Network was used to classify the seizure episodes in rats. Seizure patterns were induced by subjecting anesthetized rats to a Biological Oxygen Demand incubator at 45-47ºC for 30 to 60 ...
Sinha, Mr Rakesh Kumar
core  

A unified model for Duchenne muscular dystrophy gene involvement in cancer: context‐dependent tumour suppression and oncogenicity

FEBS Open Bio, EarlyView.
We propose a context‐dependent model where the Duchenne muscular dystrophy (DMD) gene acts as a tumour suppressor in aggressive tumours and as an oncogene in less aggressive ones. We propose this model as a unified framework to explain the opposing survival associations with DMD expression and to guide experimental exploration of the dual role of DMD ...
Lee Machado, Leanne Jones, Sonika Divakar, Michael Naidoo, Karen Anthony   +4 more
wiley   +1 more source

Short‐term actions of epigalocatechin‐3‐gallate in the liver: a mechanistic insight into hypoglycemic and potential toxic effects

FEBS Open Bio, EarlyView.
Epigallocatechin‐3‐gallate (EGCG) acutely inhibited gluconeogenesis and enhanced glycolysis, glycogenolysis, and fatty acid oxidation in perfused rat livers. Mechanistic assays revealed mitochondrial uncoupling, inhibition of pyruvate carboxylation and glucose‐6‐phosphatase, shift of NADH/NAD+ ratios toward oxidation, and loss of membrane integrity ...
Carla Indianara Bonetti, Bruna Lopes Correia, Francielle Cristina Nakamura Manicardi, Nairana Mithieli de Queiroz Eskuarek Melo, Vanesa de Oliveira Pateis, Jurandir Fernando Comar, Anacharis Babeto de Sá‐Nakanishi, Adelar Bracht, Lívia Bracht   +8 more
wiley   +1 more source

Brain-Inspired Architecture for Spiking Neural Networks

Biomimetics
Spiking neural networks (SNNs), using action potentials (spikes) to represent and transmit information, are more biologically plausible than traditional artificial neural networks.
Fengzhen Tang, Junhuai Zhang, Chi Zhang, Lianqing Liu   +3 more
doaj   +1 more source