Rhys Heffernan

2.1k total citations
15 papers, 1.5k citations indexed

About

Rhys Heffernan is a scholar working on Molecular Biology, Materials Chemistry and Computational Theory and Mathematics. According to data from OpenAlex, Rhys Heffernan has authored 15 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 7 papers in Materials Chemistry and 4 papers in Computational Theory and Mathematics. Recurrent topics in Rhys Heffernan's work include Protein Structure and Dynamics (12 papers), Machine Learning in Bioinformatics (11 papers) and Enzyme Structure and Function (7 papers). Rhys Heffernan is often cited by papers focused on Protein Structure and Dynamics (12 papers), Machine Learning in Bioinformatics (11 papers) and Enzyme Structure and Function (7 papers). Rhys Heffernan collaborates with scholars based in Australia, Fiji and China. Rhys Heffernan's co-authors include Kuldip K. Paliwal, Yuedong Yang, Yaoqi Zhou, James Lyons, Abdollah Dehzangi, Alok Sharma, Abdul Sattar, Jihua Wang, Jack Hanson and Jianzhao Gao and has published in prestigious journals such as Bioinformatics, Scientific Reports and Journal of Computational Chemistry.

In The Last Decade

Rhys Heffernan

15 papers receiving 1.5k citations

Peers

Countries citing papers authored by Rhys Heffernan

Since Specialization

Citations

This map shows the geographic impact of Rhys Heffernan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Rhys Heffernan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rhys Heffernan more than expected).

Fields of papers citing papers by Rhys Heffernan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rhys Heffernan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Rhys Heffernan. The network helps show where Rhys Heffernan may publish in the future.

Co-authorship network of co-authors of Rhys Heffernan

This figure shows the co-authorship network connecting the top 25 collaborators of Rhys Heffernan. A scholar is included among the top collaborators of Rhys Heffernan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Rhys Heffernan. Rhys Heffernan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

#	Work	Indexed citations
1	SPIN2: Predicting sequence profiles from protein structures using deep neural networks 2018 ·Proteins Structure Function and Bioinformatics ·(unknown), Zhixiu Li, Jack Hanson, Rhys Heffernan, James Lyons, Kuldip K. Paliwal, Abdollah Dehzangi, Yuedong Yang, Yaoqi Zhou	52
2	Detecting Proline and Non-Proline Cis Isomers in Protein Structures from Sequences Using Deep Residual Ensemble Learning 2018 ·Journal of Chemical Information and Modeling ·Jaswinder Singh, Jack Hanson, Rhys Heffernan, Kuldip K. Paliwal, Yuedong Yang, Yaoqi Zhou	13
3	Single‐sequence‐based prediction of protein secondary structures and solvent accessibility by deep whole‐sequence learning 2018 ·Journal of Computational Chemistry ·Rhys Heffernan, Kuldip K. Paliwal, James Lyons, Jaswinder Singh, Yuedong Yang, Yaoqi Zhou	81
4	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 2017 ·Bioinformatics ·Rhys Heffernan, Yuedong Yang, Kuldip K. Paliwal, Yaoqi Zhou	254
5	SPIDER2: A Package to Predict Secondary Structure, Accessible Surface Area, and Main-Chain Torsional Angles by Deep Neural Networks 2016 ·Methods in molecular biology ·Yuedong Yang, Rhys Heffernan, Kuldip K. Paliwal, James Lyons, Abdollah Dehzangi, Alok Sharma, Jihua Wang, Abdul Sattar, Yaoqi Zhou	132
6	Protein fold recognition using HMM–HMM alignment and dynamic programming 2016 ·Journal of Theoretical Biology ·James Lyons, Kuldip K. Paliwal, Abdollah Dehzangi, Rhys Heffernan, Tatsuhiko Tsunoda, Alok Sharma	28
7	Sixty-five years of the long march in protein secondary structure prediction: the final stretch? 2016 ·Briefings in Bioinformatics ·Yuedong Yang, Jianzhao Gao, Jihua Wang, Rhys Heffernan, Jack Hanson, Kuldip K. Paliwal, Yaoqi Zhou	171
8	Improving prediction of secondary structure, local backbone angles and solvent accessible surface area of proteins by iterative deep learning 2015 ·Scientific Reports ·Rhys Heffernan, Kuldip K. Paliwal, James Lyons, Abdollah Dehzangi, Alok Sharma, Jihua Wang, Abdul Sattar, Yuedong Yang, Yaoqi Zhou	270
9	A Short Review of Deep Learning Neural Networks in Protein Structure Prediction Problems 2015 ·Kuldip K. Paliwal, James Lyons, Rhys Heffernan	15
10	Advancing the Accuracy of Protein Fold Recognition by Utilizing Profiles From Hidden Markov Models 2015 ·IEEE Transactions on NanoBioscience ·James Lyons, Abdollah Dehzangi, Rhys Heffernan, Yuedong Yang, Yaoqi Zhou, Alok Sharma, Kuldip K. Paliwal	34
11	Highly accurate sequence-based prediction of half-sphere exposures of amino acid residues in proteins 2015 ·Bioinformatics ·Rhys Heffernan, Abdollah Dehzangi, James Lyons, Kuldip K. Paliwal, Alok Sharma, Jihua Wang, Abdul Sattar, Yaoqi Zhou, Yuedong Yang	76
12	Gram-positive and gram-negative subcellular localization using rotation forest and physicochemical-based features 2015 ·BMC Bioinformatics ·Abdollah Dehzangi, (unknown), Rhys Heffernan, Alok Sharma, James Lyons, K.K. Paliwal, Abdul Sattar	30
13	Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto‐encoder deep neural network 2014 ·Journal of Computational Chemistry ·James Lyons, Abdollah Dehzangi, Rhys Heffernan, Alok Sharma, Kuldip K. Paliwal, Abdul Sattar, Yaoqi Zhou, Yuedong Yang	118
14	Gram-positive and Gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou׳s general PseAAC 2014 ·Journal of Theoretical Biology ·Abdollah Dehzangi, Rhys Heffernan, Alok Sharma, James Lyons, Kuldip K. Paliwal, Abdul Sattar	222
15	Pattern Recognition in Bioinformatics 2014 ·Lecture notes in computer science ·Abdollah Dehzangi, Rhys Heffernan, James Lyons, Alok Sharma, Kuldip K. Paliwal, Abdul Sattar	2

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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