Computational identification of vesicular transport proteins from sequences using deep gated recurrent units architecture

Computational identification of vesicular transport proteins from sequences using deep gated recurrent units architecture

10.1016/j.csbj.2019.09.005

Saved in:

Bibliographic Details
Main Authors:	Le, N.Q.K., Yapp, E.K.Y., Nagasundaram, N., Chua, M.C.H., Yeh, H.-Y.
Other Authors:	INSTITUTE OF SYSTEMS SCIENCE
Published:	Elsevier B.V. 2021
Subjects:	Deep learning Membrane proteins Protein function prediction Recurrent neural network Transport proteins Vesicular trafficking model
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/209630
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	National University of Singapore

Similar Items

Computational identification of vesicular transport proteins from sequences using deep gated recurrent units architecture
by: Le, Nguyen Quoc Khanh, et al.
Published: (2020)

Inferring origin-destination distribution of agent transfer in a complex network using deep gated recurrent units
by: Saw, Vee-Liem, et al.
Published: (2023)

Entropic criteria for protein folding derived from recurrences: Six residues patch as the basic protein word
by: Zbilut, J.P., et al.
Published: (2011)

Advances in exploration of machine learning methods for predicting functional class and interaction profiles of proteins and peptides irrespective of sequence homology
by: Cui, J., et al.
Published: (2014)

PREDICTIVE MODELS TO DISCOVER NOVEL RNA-BINDING PROTEINS
by: JIN WENHAO
Published: (2018)

Building energy consumption raw data forecasting using data cleaning and deep recurrent neural networks
by: Yang, J., et al.
Published: (2022)

FTIP-Dependent STM Trafficking Regulates Shoot Meristem Development in Arabidopsis
by: Liu, L., et al.
Published: (2021)

Using indirect protein-protein interactions for protein complex prediction
by: Chua, H.N., et al.
Published: (2013)

Effect of training datasets on support vector machine prediction of protein-protein interactions
by: Lo, S.L., et al.
Published: (2014)

Ultrastructural characterization of endoplasmic reticulum - Golgi transport containers (EGTC)
by: Horstmann, H, et al.
Published: (2020)

The involvement of cellular components in West Nile virus replication cycle
by: CHU JANG HANN, JUSTIN
Published: (2010)

Accurate prediction of scorpion toxin functional properties from primary structures
by: Tan, P.T.J., et al.
Published: (2011)

Enzyme Family Classification by Support Vector Machines
by: Cai, C.Z., et al.
Published: (2014)

Prediction of ligand-binding proteins and their inhibitors: machine learning approach
by: LIN HONGHUANG
Published: (2014)

A survey of computational methods for protein complex prediction from protein interaction networks
by: Srihari, S., et al.
Published: (2013)

The Colorectal Cancer Recurrence Support (CARES) System
by: Ong, L.S., et al.
Published: (2014)

Protein function prediction via protein-protein interaction - a Support Vector Machine approach
by: LO SIAW LING
Published: (2010)

iMotor-CNN : identifying molecular functions of cytoskeleton motor proteins using 2D convolutional neural network via Chou's 5-step rule
by: Le, Nguyen Quoc Khanh, et al.
Published: (2021)

Protein-protein interactions prediction via multimodal deep polynomial network and regularized extreme learning machine
by: Lei, Haijun, et al.
Published: (2020)

Temporal Spiking Recurrent Neural Network for Action Recognition
by: Wang, W., et al.
Published: (2022)

Prediction of functional class of novel plant proteins by a statistical learning method
by: Han, L.Y., et al.
Published: (2014)

Homology-free prediction of functional class of proteins and peptides by support vector machines
by: Zhu, F., et al.
Published: (2014)

TMEM115 is an integral membrane protein of the Golgi complex involved in retrograde transport
by: Ong, Y.S, et al.
Published: (2020)

Protein function and inhibitor prediction by statistical learning approach
by: HAN LIANYI
Published: (2010)

ACCELERATED TRAINING OF CONSTITUTIVE RELATIONS FOR HISTORY-DEPENDENT COMPOSITE MATERIALS USING RECURRENT NEURAL NETWORK WITH TRANSFER LEARNING
by: ZHANG CHEN
Published: (2023)

Training issues and learning algorithms for feedforward and recurrent neural networks
by: TEOH EU JIN
Published: (2010)

Effect of training datasets on support vector machine prediction of protein-protein interactions
by: LO, Siaw Ling, et al.
Published: (2005)

Dimension reduction in recurrent networks by canonicalization
by: Grigoryeva, Lyudmila, et al.
Published: (2022)

Binding modes of teixobactin to lipid ii : molecular dynamics study
by: Liu, Yang, et al.
Published: (2018)

Disease gene classification with metagraph representations
by: KIRCALI ATA, Sezin, et al.
Published: (2018)

Disease gene classification with metagraph representations
by: KIRCALI ATA, Sezin, et al.
Published: (2017)

Clustering-based approach for predicting motif pairs from protein interaction data
by: Leung, H.C.-M., et al.
Published: (2013)

Understanding Dengue Virus Capsid Protein Interaction with Key Biological Targets
by: Faustino, A.F, et al.
Published: (2020)

Integrin-beta3 clusters recruit clathrin-mediated endocytic machinery in the absence of traction force
by: Yu, C.-H, et al.
Published: (2020)

Global convergence of Lotka-Volterra recurrent neural networks with delays
by: Yi, Z., et al.
Published: (2014)

Protein structure and fold prediction using Tree-Augmented naïve Bayesian classifier
by: Chinnasamy, A., et al.
Published: (2013)

Multi-step down-regulation of the secretory pathway in mitosis: A fresh perspective on protein trafficking
by: Yeong, F.M.
Published: (2014)

Mammalian Bet3 functions as a cytosolic factor participating in transport from the ER to the Golgi apparatus
by: Loh, E, et al.
Published: (2020)

Molecular nonlinear dynamics and protein thermal uncertainty quantification
by: Xia, Kelin, et al.
Published: (2016)

Robust learning and control of time-delay nonlinear systems with deep recurrent Koopman operators
by: Han, Minghao, et al.
Published: (2024)