| 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, 2017 | 274 | 2017 |
| 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, 2018 | 259 | 2018 |
| RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning J Singh, J Hanson, K Paliwal, Y Zhou Nature communications 10 (1), 5407, 2019 | 257 | 2019 |
| Critical assessment of protein intrinsic disorder prediction M Necci, D Piovesan, SCE Tosatto Nature methods 18 (5), 472-481, 2021 | 179 | 2021 |
| 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 | 178 | 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 | 163 | 2018 |
| SPOT-Disorder2: improved protein intrinsic disorder prediction by ensembled deep learning J Hanson, KK Paliwal, T Litfin, Y Zhou Genomics, proteomics & bioinformatics 17 (6), 645-656, 2019 | 112 | 2019 |
| 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 | 79 | 2018 |
| 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 | 68 | 2018 |
| DEPICTER: intrinsic disorder and disorder function prediction server A Barik, A Katuwawala, J Hanson, K Paliwal, Y Zhou, L Kurgan Journal of molecular biology 432 (11), 3379-3387, 2020 | 50 | 2020 |
| Identifying molecular recognition features in intrinsically disordered regions of proteins by transfer learning J Hanson, T Litfin, K Paliwal, Y Zhou Bioinformatics 36 (4), 1107-1113, 2020 | 43 | 2020 |
| Large expert-curated database for benchmarking document similarity detection in biomedical literature search P Brown, AC Tan, MA El-Esawi, T Liehr, O Blanck, DP Gladue, ... Database 2019, 2019 | 26 | 2019 |
| Getting to know your neighbor: protein structure prediction comes of age with contextual machine learning J Hanson, KK Paliwal, T Litfin, Y Yang, Y Zhou Journal of Computational Biology 27 (5), 796-814, 2020 | 19 | 2020 |
| 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 | 17 | 2018 |
| 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 | 12 | 2018 |
| SPOT‐Fold: Fragment‐Free Protein Structure Prediction Guided by Predicted Backbone Structure and Contact Map Y Cai, X Li, Z Sun, Y Lu, H Zhao, J Hanson, K Paliwal, T Litfin, Y Zhou, ... Journal of Computational Chemistry 41 (8), 745-750, 2020 | 10 | 2020 |
| CAID prediction portal: a comprehensive service for predicting intrinsic disorder and binding regions in proteins A Del Conte, A Bouhraoua, M Mehdiabadi, D Clementel, AM Monzon, ... Nucleic Acids Research, gkad430, 2023 | 7 | 2023 |
| Protein Structure Prediction by Recurrent and Convolutional Deep Neural Network Architectures J Hanson Nov, 2018 | 1 | 2018 |
Kuldip PaliwalProfessor (Chair, Communication and Information Engineering), Griffith University, BrisbaneVerified email at griffith.edu.au
