Yaoqi Zhou

Yaoqi Zhou publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Yaoqi Zhou sits on this spectrum.

Yaoqi Zhou D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Yaoqi Zhou sits on this spectrum.

Research.com Recognitions

• 2025 - Research.com Computer Science in Australia Leader Award
• 2022 - Research.com Computer Science in Australia Leader Award

Overview

Best Publications

• 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 K. Paliwal;Yaoqi Zhou

  455
  Citations

• Real-time reliable determination of binding kinetics of DNA hybridization using a multi-channel graphene biosensor

  Shicai Xu;Jian Zhan;Baoyuan Man;Shouzhen Jiang

  438
  Citations

• Improving protein fold recognition and template-based modeling by employing probabilistic-based matching between predicted one-dimensional structural properties of query and corresponding native properties of templates

  Yuedong Yang;Eshel Faraggi;Huiying Zhao;Yaoqi Zhou

  431
  Citations

• RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning.

  Jaswinder Singh;Jack Hanson;Kuldip Paliwal;Yaoqi Zhou

  425
  Citations

• Improving prediction of secondary structure, local backbone angles, and solvent accessible surface area of proteins by iterative deep learning.

  Rhys Heffernan;Kuldip Paliwal;James Lyons;Abdollah Dehzangi

  407
  Citations

• Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks.

  Jack Hanson;Yuedong Yang;Kuldip K. Paliwal;Yaoqi Zhou

  315
  Citations

• Protein binding site prediction using an empirical scoring function

  Shide Liang;Chi Zhang;Song Liu;Yaoqi Zhou

  312
  Citations

• Fold recognition by combining sequence profiles derived from evolution and from depth‐dependent structural alignment of fragments

  Hongyi Zhou;Yaoqi Zhou

  294
  Citations

• SPINE X: Improving protein secondary structure prediction by multistep learning coupled with prediction of solvent accessible surface area and backbone torsion angles

  Eshel Faraggi;Tuo Zhang;Tuo Zhang;Yuedong Yang;Yuedong Yang;Lukasz A. Kurgan;Lukasz A. Kurgan

  290
  Citations

• Sixty-five years of the long march in protein secondary structure prediction: the final stretch?

  Yuedong Yang;Jianzhao Gao;Jihua Wang;Rhys Heffernan

  281
  Citations

• Single-body residue-level knowledge-based energy score combined with sequence-profile and secondary structure information for fold recognition

  Hongyi Zhou;Yaoqi Zhou

  228
  Citations

• 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

  Jack Hanson;Kuldip K. Paliwal;Thomas Litfin;Yuedong Yang

  223
  Citations

• Folding rate prediction using total contact distance.

  Hongyi Zhou;Yaoqi Zhou

  223
  Citations

• SPINE-D: Accurate Prediction of Short and Long Disordered Regions by a Single Neural-Network Based Method

  Tuo Zhang;Eshel Faraggi;Bin Xue;A. Keith Dunker

  205
  Citations

• Accurate prediction of protein contact maps by coupling residual two-dimensional bidirectional long short-term memory with convolutional neural networks.

  Jack Hanson;Kuldip K. Paliwal;Thomas Litfin;Yuedong Yang;Yuedong Yang

  197
  Citations

• Achieving 80% ten‐fold cross‐validated accuracy for secondary structure prediction by large‐scale training

  Ofer Dor;Yaoqi Zhou

  189
  Citations

• SPIDER2: A Package to Predict Secondary Structure, Accessible Surface Area, and Main-Chain Torsional Angles by Deep Neural Networks

  Yuedong Yang;Rhys Heffernan;Kuldip Paliwal;James Lyons

  187
  Citations

• Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto-encoder deep neural network.

  James G. Lyons;Abdollah Dehzangi;Abdollah Dehzangi;Rhys Heffernan;Alok Sharma;Alok Sharma

  180
  Citations

• Structure-aware protein-protein interaction site prediction using deep graph convolutional network.

  Qianmu Yuan;Jianwen Chen;Huiying Zhao;Yaoqi Zhou

  178
  Citations

• SPOT-Disorder2: Improved Protein Intrinsic Disorder Prediction by Ensembled Deep Learning

  Jack Hanson;Kuldip K. Paliwal;Thomas Litfin;Yaoqi Zhou

  164
  Citations

• Community-wide assessment of protein-interface modeling suggests improvements to design methodology

  Sarel J. Fleishman;Sarel J. Fleishman;Timothy A. Whitehead;Eva Maria Strauch;Jacob E. Corn;Jacob E. Corn

  156
  Citations

• Improving the prediction accuracy of residue solvent accessibility and real-value backbone torsion angles of proteins by guided-learning through a two-layer neural network.

  Eshel Faraggi;Bin Xue;Bin Xue;Yaoqi Zhou;Yaoqi Zhou

  150
  Citations