Jack Hanson
Orcid: 0000-0001-5105-8497
According to our database1,
Jack Hanson
authored at least 13 papers
between 2017 and 2023.
Collaborative distances:
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Bibliography
2023
CAID prediction portal: a comprehensive service for predicting intrinsic disorder and binding regions in proteins.
Nucleic Acids Res., July, 2023
Using Worker Position Data for Human-Driven Decision Support in Labour-Intensive Manufacturing.
Sensors, 2023
Design of a Serious Game for Safety in Manufacturing Industry Using Hybrid Simulation Modelling: Towards Eliciting Risk Preferences.
Proceedings of the Winter Simulation Conference, 2023
2020
SPOT-Fold: Fragment-Free Protein Structure Prediction Guided by Predicted Backbone Structure and Contact Map.
J. Comput. Chem., 2020
Getting to Know Your Neighbor: Protein Structure Prediction Comes of Age with Contextual Machine Learning.
J. Comput. Biol., 2020
Identifying molecular recognition features in intrinsically disordered regions of proteins by transfer learning.
Bioinform., 2020
2019
SPOT-Disorder2: Improved Protein Intrinsic Disorder Prediction by Ensembled Deep Learning.
Genom. Proteom. Bioinform., 2019
Improving prediction of protein secondary structure, backbone angles, solvent accessibility and contact numbers by using predicted contact maps and an ensemble of recurrent and residual convolutional neural networks.
Bioinform., 2019
2018
Detecting Proline and Non-Proline Cis Isomers in Protein Structures from Sequences Using Deep Residual Ensemble Learning.
J. Chem. Inf. Model., 2018
Accurate Single-Sequence Prediction of Protein Intrinsic Disorder by an Ensemble of Deep Recurrent and Convolutional Architectures.
J. Chem. Inf. Model., 2018
Accurate prediction of protein contact maps by coupling residual two-dimensional bidirectional long short-term memory with convolutional neural networks.
Bioinform., 2018
Sixty-five years of the long march in protein secondary structure prediction: the final stretch?
Briefings Bioinform., 2018
2017
Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks.
Bioinform., 2017