Results 71 to 80 of about 349,230 (288)
Learning text representation using recurrent convolutional neural network with highway layers [PDF]
, 2016 Recently, the rapid development of word embedding and neural networks has brought new inspiration to various NLP and IR tasks. In this paper, we describe a staged hybrid model combining Recurrent Convolutional Neural Networks (RCNN) with highway layers ...
Luo, Rui +3 more
core +1 more source
Molecular determinants of signal transduction in tropomyosin receptor kinases
FEBS Open Bio, EarlyView.Tropomyosin receptor kinases control critical neuronal functions, but how do the same receptors produce diverse cellular responses? This review explores the structural mechanisms behind Trk signaling diversity, focusing on allosteric modulation and ligand bias.
Giray Enkavi
wiley +1 more source
EMP response modeling of TVS based on the recurrent neural network
Journal of Hebei University of Science and Technology, 2015 Due to the larger workload in the implementation process and the poor consistence between the test results and actual situation problems when using the transmission line pulse (TLP) testing methods, a modeling method based on the recurrent neural network
Zhiqiang JI +3 more
doaj +1 more source
Naked cuticle is essential for Drosophila wing development beyond Wingless signaling
FEBS Open Bio, EarlyView.Naked cuticle (Nkd), a Wnt signaling inhibitor, assumes extensive roles in Drosophila wing development. Overexpressing Nkd causes smaller, crumpled wings, while also perturbing multiple signaling pathways and developmental genes. A specific region (R1S) is critical for Nkd's function as a signaling integrator, offering new insights for studying its ...
Rui Wang, Ping Wang
wiley +1 more source
FEBS Open Bio, EarlyView.KLK7, a tissue kallikrein‐related peptidase, is elevated in advanced colorectal cancer and associated with shorter survival. High KLK7 levels in ascites correlate with peritoneal metastasis. In mice, KLK7 overexpression increases metastasis. In vitro, KLK7 enhances cancer cell proliferation, migration, adhesion, and spheroid formation, driving ...
Yosr Z. Haffani +6 more
wiley +1 more source
MathematicsThis paper presents a varying-parameter finite-time recurrent neural network, called a varying-factor finite-time recurrent neural network (VFFTRNN), which is able to solve the solution of the time-varying Sylvester equation online.
Haoming Tan +6 more
doaj +1 more source
The Power of Linear Recurrent Neural Networks
, 2020 Recurrent neural networks are a powerful means to cope with time series. We show how a type of linearly activated recurrent neural networks, which we call predictive neural networks, can approximate any time-dependent function f(t) given by a number of ...
Litz, Sandra +3 more
core
Genetically Generated Neural Networks I: Representational Effects [PDF]
, 1992 This paper studies several applications of genetic algorithms (GAs) within the neural networks field. After generating a robust GA engine, the system was used to generate neural network circuit architectures.
Marti, Leonardo
core +2 more sources
BMI‐1 modulation and trafficking during M phase in diffuse intrinsic pontine glioma
FEBS Open Bio, EarlyView.The schematic illustrates BMI‐1 phosphorylation during M phase, which triggers its translocation from the nucleus to the cytoplasm. In cycling cells, BMI‐1 functions within the PRC1 complex to mediate H2A K119 monoubiquitination. Following PTC596‐induced M phase arrest, phosphorylated BMI‐1 dissociates from PRC1 and is exported to the cytoplasm via its
Banlanjo Umaru +6 more
wiley +1 more source
IEEE Access, 2020 Sentiment analysis studies in the literature mostly use either recurrent or recursive neural network models. Recurrent models capture the effect of time and propagate the information of sentiment labels in a review throughout the word sequence. Recursive
Cem Rifki Aydin, Tunga Gungor
doaj +1 more source