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Bioinformatics (Oxford, England)
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April 22, 2017
Capturing non-local interactions by long short-term memory bidirectional recurrent neural networks for improving prediction of protein secondary structure, backbone angles, contact numbers and solvent accessibility
Rhys Heffernan, Yuedong Yang, Kuldip Paliwal, et al.
Journal of Chemical Information and Modeling
|
August 18, 2018
Detecting Proline and Non-Proline Cis Isomers in Protein Structures from Sequences Using Deep Residual Ensemble Learning
Jaswinder Singh, Jack Hanson, Rhys Heffernan, et al.
Journal of Theoretical Biology
|
September 30, 2014
Gram-positive and Gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou׳s general PseAAC
Abdollah Dehzangi, Rhys Heffernan, Alok Sharma, et al.
Journal of Computational Chemistry
|
October 29, 2018
Single-sequence-based prediction of protein secondary structures and solvent accessibility by deep whole-sequence learning
Rhys Heffernan, Kuldip Paliwal, James Lyons, et al.
Journal of Theoretical Biology
|
January 24, 2016
Protein fold recognition using HMM-HMM alignment and dynamic programming
James Lyons, Kuldip K Paliwal, Abdollah Dehzangi, et al.
IEEE Transactions on Nanobioscience
|
July 25, 2015
Advancing the Accuracy of Protein Fold Recognition by Utilizing Profiles From Hidden Markov Models
James Lyons, Abdollah Dehzangi, Rhys Heffernan, et al.
Briefings in Bioinformatics
|
January 2, 2017
Sixty-five years of the long march in protein secondary structure prediction: the final stretch?
Yuedong Yang, Jianzhao Gao, Jihua Wang, et al.
BMC Bioinformatics
|
March 4, 2015
Gram-positive and Gram-negative subcellular localization using rotation forest and physicochemical-based features
Abdollah Dehzangi, Sohrab Sohrabi, Rhys Heffernan, et al.
Journal of Computational Chemistry
|
September 13, 2014
Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto-encoder deep neural network
James Lyons, Abdollah Dehzangi, Rhys Heffernan, et al.
Proteins
|
March 7, 2018
SPIN2: Predicting sequence profiles from protein structures using deep neural networks
James O'Connell, Zhixiu Li, Jack Hanson, et al.
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Showing results (1-10 of 12) with videos related to
Sort By:
Page
of 2
Bioinformatics (Oxford, England)
|
April 22, 2017
Capturing non-local interactions by long short-term memory bidirectional recurrent neural networks for improving prediction of protein secondary structure, backbone angles, contact numbers and solvent accessibility
Rhys Heffernan, Yuedong Yang, Kuldip Paliwal, et al.
Journal of Chemical Information and Modeling
|
August 18, 2018
Detecting Proline and Non-Proline Cis Isomers in Protein Structures from Sequences Using Deep Residual Ensemble Learning
Jaswinder Singh, Jack Hanson, Rhys Heffernan, et al.
Journal of Theoretical Biology
|
September 30, 2014
Gram-positive and Gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou׳s general PseAAC
Abdollah Dehzangi, Rhys Heffernan, Alok Sharma, et al.
Journal of Computational Chemistry
|
October 29, 2018
Single-sequence-based prediction of protein secondary structures and solvent accessibility by deep whole-sequence learning
Rhys Heffernan, Kuldip Paliwal, James Lyons, et al.
Journal of Theoretical Biology
|
January 24, 2016
Protein fold recognition using HMM-HMM alignment and dynamic programming
James Lyons, Kuldip K Paliwal, Abdollah Dehzangi, et al.
IEEE Transactions on Nanobioscience
|
July 25, 2015
Advancing the Accuracy of Protein Fold Recognition by Utilizing Profiles From Hidden Markov Models
James Lyons, Abdollah Dehzangi, Rhys Heffernan, et al.
Briefings in Bioinformatics
|
January 2, 2017
Sixty-five years of the long march in protein secondary structure prediction: the final stretch?
Yuedong Yang, Jianzhao Gao, Jihua Wang, et al.
BMC Bioinformatics
|
March 4, 2015
Gram-positive and Gram-negative subcellular localization using rotation forest and physicochemical-based features
Abdollah Dehzangi, Sohrab Sohrabi, Rhys Heffernan, et al.
Journal of Computational Chemistry
|
September 13, 2014
Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto-encoder deep neural network
James Lyons, Abdollah Dehzangi, Rhys Heffernan, et al.
Proteins
|
March 7, 2018
SPIN2: Predicting sequence profiles from protein structures using deep neural networks
James O'Connell, Zhixiu Li, Jack Hanson, et al.
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of 2