Jack Hanson
Jack Hanson
Signal Processing Laboratory, Griffith University
Verified email at griffithuni.edu.au
TitleCited byYear
Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks
J Hanson, Y Yang, K Paliwal, Y Zhou
Bioinformatics 33 (5), 685-692, 2016
452016
Sixty-five years of the long march in protein secondary structure prediction: the final stretch?
Y Yang, J Gao, J Wang, R Heffernan, J Hanson, K Paliwal, Y Zhou
Briefings in bioinformatics 19 (3), 482-494, 2016
402016
Accurate Prediction of Protein Contact Maps by Coupling Residual Two-Dimensional Bidirectional Long Short-Term Memory with Convolutional Neural Networks
J Hanson, K Paliwal, T Litfin, Y Yang, Y Zhou
Bioinformatics, 2018
52018
Detecting Proline and Non-Proline Cis Isomers in Protein Structures from Sequences Using Deep Residual Ensemble Learning
J Singh, J Hanson, R Heffernan, K Paliwal, Y Yang, Y Zhou
Journal of chemical information and modeling 58 (9), 2033-2042, 2018
22018
SPIN2: Predicting sequence profiles from protein structures using deep neural networks
J O'Connell, Z Li, J Hanson, R Heffernan, J Lyons, K Paliwal, A Dehzangi, ...
Proteins: Structure, Function, and Bioinformatics 86 (6), 629-633, 2018
22018
Spectral subband centroids for robust speaker identification using marginalization-based missing feature theory
A Nicolson, J Hanson, J Lyons, K Paliwal
International Journal of Signal Processing Systems 6 (1), 12-16, 2018
12018
Accurate Single-Sequence Prediction of Protein Intrinsic Disorder by an Ensemble of Deep Recurrent and Convolutional Architectures
J Hanson, K Paliwal, Y Zhou
Journal of chemical information and modeling 58 (11), 2369-2376, 2018
2018
Improving prediction of protein secondary structure, backbone angles, solvent accessibility and contact numbers by using predicted contact maps and an ensemble of recurrent and …
J Hanson, KK Paliwal, T Litfin, Y Yang, Y Zhou
Bioinformatics, 2018
2018
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Articles 1–8