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Toplam kayıt 53, listelenen: 31-40
DEEPred: Automated Protein Function Prediction with Multi-task Feed-forward Deep Neural Networks
(Nature Publishing Group, 2019)
Automated protein function prediction is critical for the annotation of uncharacterized protein sequences, where accurate prediction methods are still required. Recently, deep learning based methods have outperformed ...
ECPred: a tool for the prediction of the enzymatic functions of protein sequences based on the EC nomenclature
(BMC, 2018)
Background: The automated prediction of the enzymatic functions of uncharacterized proteins is a crucial topic in bioinformatics. Although several methods and tools have been proposed to classify enzymes, most of these ...
Differential convolutional neural network
(Elsevier, 2019)
Convolutional neural networks with strong representation ability of deep structures have ever increasing popularity in many research areas. The main difference of Convolutional Neural Networks with respect to existing ...
Large-scale automated function prediction of protein sequences and an experimental case study validation on PTEN transcript variants
(Wiley, 2018)
Recent advances in computing power and machine learning empower functional annotation of protein sequences and their transcript variations. Here, we present an automated prediction system UniGOPred, for GO annotations and ...
A fully distributed energy-aware multi-level clustering and routing for WSN-based IoT
(Wiley, 2021)
One of the major problems in wireless sensor networks (WSNs) is that resource-constrained sensor nodes consume their limited batteries quickly due to long-distance data communications. The communication distance of the ...
Deep Learning with ConvNet Predicts Imagery Tasks Through EEG
(Springer, 2021)
Deep learning with convolutional neural networks (ConvNets) has dramatically improved the learning capabilities of computer vision applications just through considering raw data without any prior feature extraction. Nowadays, ...
Multihop routing with static and distributed clustering in WSNs
(Springer, 2021)
Nowadays, Wireless Sensor Networks are one of the fundamental infrastructures for IoT technology. Although WSN has been researched for a decade, providing energy efficiency for resource-constrained sensor nodes is still a ...
MOS-C Based Electronically Tuneable Current/Voltage-Mode Third Order Quadrature Oscillator and Biquadratic Filter Realization
(Kauno Technologijos Universitetas, 2021)
This paper introduces a new electronically tuneable third order quadrature oscillator and biquadratic filter with MOS-C realization using all grounded passive components. Voltage-mode second order low-pass, high-pass, ...
Prediction of Li-Ion Battery Discharge Patterns in IoT Devices Under Random Use Via Machine Learning Algorithms
(Oxford University Press, 2022)
This study presents foreseeing of the Lithium-ion battery discharge models for the Internet of Things (IoT) devices under randomized use patterns. IoT systems run in harmony with the human-machine interface, communication ...
A novel fractional operator application for neural networks using proportional Caputo derivative
(Springer, 2022)
In machine learning models, one of the most popular models is artificial neural networks. The activation function is one of the important parameters of neural networks. In this paper, the sigmoid function is used as an ...