about
Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications.Evaluation of residue-residue contact prediction in CASP10Formulation of probabilistic models of protein structure in atomic detail using the reference ratio method.Gene expression inference with deep learning.A study and benchmark of DNcon: a method for protein residue-residue contact prediction using deep networks.Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning ModelPCP-ML: protein characterization package for machine learning.Improving prediction of secondary structure, local backbone angles, and solvent accessible surface area of proteins by iterative deep learning.Protein contact prediction by integrating joint evolutionary coupling analysis and supervised learning.Protein Residue Contacts and Prediction MethodsA large-scale comparative assessment of methods for residue-residue contact prediction.ConEVA: a toolbox for comprehensive assessment of protein contacts.Deep learning for computational chemistry.The evolution of logic circuits for the purpose of protein contact map predictionA deep learning framework for improving long-range residue-residue contact prediction using a hierarchical strategy.Membrane protein contact and structure prediction using co-evolution in conjunction with machine learning.CNNcon: improved protein contact maps prediction using cascaded neural networks.Deep architectures and deep learning in chemoinformatics: the prediction of aqueous solubility for drug-like molecules.Characteristics of protein residue-residue contacts and their application in contact predictionA new ensemble coevolution system for detecting HIV-1 protein coevolution.A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction.Combining physicochemical and evolutionary information for protein contact prediction.Improved contact predictions using the recognition of protein like contact patternsDid α-Synuclein and Glucocerebrosidase Coevolve? Implications for Parkinson's Disease.Predicting protein residue-residue contacts using deep networks and boostingMarkov state models of protein misfoldingPredicting protein contact map using evolutionary and physical constraints by integer programming.What time is it? Deep learning approaches for circadian rhythms.CoinFold: a web server for protein contact prediction and contact-assisted protein foldingHigh-accuracy prediction of transmembrane inter-helix contacts and application to GPCR 3D structure modeling.Sequence-based Gaussian network model for protein dynamics.Predicting accurate contacts in thousands of Pfam domain families using PconsC3.The Next Era: Deep Learning in Pharmaceutical Research.Deep learning in bioinformatics.Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks.R2C: improving ab initio residue contact map prediction using dynamic fusion strategy and Gaussian noise filter.Detecting Cardiovascular Disease from Mammograms With Deep Learning.Deep learning of the tissue-regulated splicing code.Observation selection bias in contact prediction and its implications for structural bioinformaticsA Template-Based Protein Structure Reconstruction Method Using Deep Autoencoder Learning.
P2860
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P2860
description
2012 nî lūn-bûn
@nan
2012 թուականի Յուլիսին հրատարակուած գիտական յօդուած
@hyw
2012 թվականի հուլիսին հրատարակված գիտական հոդված
@hy
2012年の論文
@ja
2012年論文
@yue
2012年論文
@zh-hant
2012年論文
@zh-hk
2012年論文
@zh-mo
2012年論文
@zh-tw
2012年论文
@wuu
name
Deep architectures for protein contact map prediction
@ast
Deep architectures for protein contact map prediction
@en
type
label
Deep architectures for protein contact map prediction
@ast
Deep architectures for protein contact map prediction
@en
prefLabel
Deep architectures for protein contact map prediction
@ast
Deep architectures for protein contact map prediction
@en
P2860
P356
P1433
P1476
Deep architectures for protein contact map prediction
@en
P2093
Ken Nagata
Pietro Di Lena
P2860
P304
P356
10.1093/BIOINFORMATICS/BTS475
P407
P50
P577
2012-07-30T00:00:00Z