Results 81 to 90 of about 1,858,056 (293)
Molecular Oncology, EarlyView.Arginine methylation can be viewed as a persistence‐prone post‐translational modification regulated by a network of PRMTs. Competitive and compensatory interactions among PRMTs can redistribute methylation across substrate pools shaped by sequence, structural, spatial, and environmental layers, reinforcing RNA‐processing, chromatin, and signaling ...
So Hyun Kwon, Ji Min Lee
wiley +1 more source
Reservoir computing with output feedback [PDF]
, 2011 Reinhart RF. Reservoir computing with output feedback. Bielefeld: Bielefeld University; 2011.A dynamical system approach to forward and inverse modeling is proposed. Forward and inverse models are trained in associative recurrent neural networks that are
Reinhart, René Felix, Reinhart, Felix
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Personal‐specific gait recognition based on latent orthogonal feature space
Cognitive Computation and Systems, 2021 Exoskeleton has been applied in the field of medical rehabilitation and assistance. However, there are still some problems in the interaction between human and exoskeleton, such as time delay, the existence of certain constraints on the human body, and ...
Quan Zhou +7 more
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FEBS Open Bio, EarlyView.Drugs previously repurposed to target blood cancers reduced neuroblastoma and glioblastoma cell growth and viability. However, their levels of anticancer activity were different and their clinical application may be problematic due to side effects at effective doses.
Abhishek Kharawatkar +4 more
wiley +1 more source
Method for functional state recognition of multifunction radars based on recurrent neural networks
IET Radar, Sonar & Navigation, 2021 Radar signal recognition plays a vital role in electronic warfare. For the multifunction radars (MFRs) with complex dynamical modes, the signal recognition needs to identify not only the emitter but also its current functional state. Existing research on
Xinsong Xu, Daping Bi, Jifei Pan
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Tustin neural networks: a class of recurrent nets for adaptive MPC of mechanical systems
IFAC-PapersOnLine, 2020 The use of recurrent neural networks to represent the dynamics of unstable systems is difficult due to the need to properly initialize their internal states, which in most of the cases do not have any physical meaning, consequent to the non-smoothness of the optimization problem.
Simone Pozzoli +2 more
openaire +3 more sources
Directed evolution of enzymes at the crossroads of tradition and innovation
FEBS Open Bio, EarlyView.An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova +2 more
wiley +1 more source
A Connectionist Model of Spatial Knowledge Acquisition in a Virtual Environment [PDF]
, 2003 This paper proposes the use of neural networks as a tool for studying navigation within virtual worlds. Results indicate that network learned to predict the next step for a given trajectory, acquiring also basic spatial knowledge in terms of landmarks ...
Sas, Corina, O'Hare, G.M.P., Reilly, R.
core +4 more sources
Automatic Generation of News Comments Based on Gated Attention Neural Networks
IEEE Access, 2018 With the development of recurrent neural networks (RNN), various natural language generation (NLG) tasks have boomed in the past few years, such as response generation in conversation and poetry generation.
Hai-Tao Zheng +3 more
doaj +1 more source
Water quality prediction method based on preferred classification
IET Cyber-Physical Systems, 2020 Water quality monitoring and prediction are important parts of Cyber Physical Systems. Considering the complexity, diversity, and strong non-linearity of water quality data, a single water quality prediction model is difficult to have a significant ...
Liming Sheng +4 more
doaj +1 more source