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Yaoqi Zhou
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Computer Science
Australia
2025

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 65 2501 2424 75 74 174 12733

Yaoqi Zhou publications per year

The chart shows the history of publications by Yaoqi Zhou between 1967 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Yaoqi Zhou published across 59 years, from 1967 to 2025, averaging 6 papers a year. Output peaked at 30 publications in 2023. 33 of the 355 publications appeared in the last two years.

No. of publications
10 20 30
Bar chart. Horizontal axis: year, 1967 to 2025. Vertical axis: number of publications, 0 to 30. Peak 30 publications in 2023. 1967: 1 publication 1968: 0 publications 1969: 0 publications 1970: 0 publications 1971: 0 publications 1972: 0 publications 1973: 0 publications 1974: 0 publications 1975: 0 publications 1976: 0 publications 1977: 0 publications 1978: 0 publications 1979: 0 publications 1980: 0 publications 1981: 0 publications 1982: 0 publications 1983: 0 publications 1984: 0 publications 1985: 0 publications 1986: 0 publications 1987: 0 publications 1988: 5 publications 1989: 9 publications 1990: 2 publications 1991: 3 publications 1992: 4 publications 1993: 1 publication 1994: 0 publications 1995: 7 publications 1996: 3 publications 1997: 3 publications 1998: 2 publications 1999: 4 publications 2000: 3 publications 2001: 3 publications 2002: 8 publications 2003: 4 publications 2004: 12 publications 2005: 11 publications 2006: 8 publications 2007: 6 publications 2008: 7 publications 2009: 10 publications 2010: 4 publications 2011: 11 publications 2012: 5 publications 2013: 7 publications 2014: 13 publications 2015: 3 publications 2016: 17 publications 2017: 19 publications 2018: 17 publications 2019: 22 publications 2020: 13 publications 2021: 23 publications 2022: 22 publications 2023: 30 publications 2024: 14 publications 2025: 19 publications
1967 2025

355 publications in total across all disciplines

View publications per year as a table
Yaoqi Zhou: publications per year, 1967 to 2025
Year Publications
1967 1
1968 0
1969 0
1970 0
1971 0
1972 0
1973 0
1974 0
1975 0
1976 0
1977 0
1978 0
1979 0
1980 0
1981 0
1982 0
1983 0
1984 0
1985 0
1986 0
1987 0
1988 5
1989 9
1990 2
1991 3
1992 4
1993 1
1994 0
1995 7
1996 3
1997 3
1998 2
1999 4
2000 3
2001 3
2002 8
2003 4
2004 12
2005 11
2006 8
2007 6
2008 7
2009 10
2010 4
2011 11
2012 5
2013 7
2014 13
2015 3
2016 17
2017 19
2018 17
2019 22
2020 13
2021 23
2022 22
2023 30
2024 14
2025 19
Total 355
Download as CSV

Yaoqi Zhou publications per year - data summary

  • Yaoqi Zhou, a Computer Science scholar from Griffith University, has 355 publications recorded across 59 years, from 1967 to 2025.
  • The oldest publication on record dates to 1967 and the most recent to 2025.
  • The most productive year is 2023, with 30 publications.
  • The least productive years with any output are 1967 and 1993, with 1 publication each.
  • 21 of the 59 years in the span carry no publications at all (1968, 1969, 1970, 1971 and others).
  • The rate of publication averages 6.0 papers per year over the whole span, or 9.3 per year counting only the 38 years with at least one publication.
  • The last 5 years on the chart (2021-2025) hold 108 publications, 30% of the career total.
  • Split into equal eras - 1967-1986: 1 publication (0.1 per year); 1987-2006: 92 publications (4.6 per year); 2007-2025: 262 publications (13.8 per year).
  • Comparing the opening and closing eras, the overall trend of publication is rising.

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.

No. of scientists
200 400 600
Bar chart with 97 bars. Horizontal axis: publications, 32–41 to 991+. Vertical axis: number of scientists, 0 to 609. Most scientists, 609, have 142–151 publications. The last bar groups every scientist with 991 publications or more. The highlighted bar, 172–181 publications, is where this scientist sits. 32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32–41 publications 991+

This scientist: 174 publications — 36th percentile

36% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

View publications distribution as a table
Number of Computer Science scientists by publication count, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
Publications Scientists This scientist
32–41 7
42–51 22
52–61 82
62–71 134
72–81 249
82–91 324
92–101 421
102–111 420
112–121 497
122–131 544
132–141 555
142–151 609
152–161 559
162–171 534
172–181 556 174
182–191 583
192–201 519
202–211 508
212–221 490
222–231 437
232–241 423
242–251 408
252–261 377
262–271 301
272–281 335
282–291 320
292–301 293
302–311 250
312–321 238
322–331 206
332–341 209
342–351 208
352–361 162
362–371 176
372–381 127
382–391 158
392–401 128
402–411 104
412–421 94
422–431 99
432–441 83
442–451 108
452–461 73
462–471 77
472–481 69
482–491 84
492–501 62
502–511 54
512–521 57
522–531 51
532–541 51
542–551 32
552–561 38
562–571 28
572–581 43
582–591 33
592–601 41
602–611 32
612–621 28
622–631 25
632–641 27
642–651 17
652–661 20
662–671 17
672–681 15
682–691 14
692–701 21
702–711 13
712–721 12
722–731 19
732–741 14
742–751 12
752–761 10
762–771 10
772–781 11
782–791 10
792–801 11
802–811 8
812–821 8
822–831 7
832–841 11
842–851 10
852–861 5
862–871 9
872–881 4
882–891 6
892–901 3
902–911 6
912–921 3
922–931 2
932–941 2
942–951 2
952–961 3
962–971 3
972–981 3
982–990 5
991+ 100
Download as CSV

Yaoqi Zhou publication distribution in Computer Science in 2026 - data summary

  • The chart plots the publication count of all 14,188 Computer Science scientists ranked by Research.com in 2026, grouped into 97 ranges running from 32–41 to 991+ publications.
  • Yaoqi Zhou, a Computer Science scholar from Griffith University, records 174 publications - the 36th percentile of the discipline.
  • 36% of ranked Computer Science scientists score the same or lower than Yaoqi Zhou, and about 64% score higher.
  • The median of the discipline falls in the 202–211 publications range, and Yaoqi Zhou ranks below the median.
  • The most crowded range is 142–151 publications, holding 609 scientists (4% of the field).
  • 70% of the field sits in the lowest quarter of the value range (up to 272–281 publications), so the distribution is heavily right-skewed and high scores are rare.
  • The final bar has no upper bound: it groups every scientist with 991 publications or more, 100 scientists in all (<1% of the field).

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.

No. of scientists
200 400 600 800
Bar chart with 52 bars. Horizontal axis: D-Index, 30–31 to 131+. Vertical axis: number of scientists, 0 to 990. Most scientists, 990, have 36–37 D-Index. The last bar groups every scientist with 131 D-Index or more. The highlighted bar, 64–65 D-Index, is where this scientist sits. 30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30–31 D-Index 131+

This scientist: 65 D-Index — 83rd percentile

83% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

View D-Index distribution as a table
Number of Computer Science scientists by D-index, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
D-Index Scientists This scientist
30–31 879
32–33 983
34–35 918
36–37 990
38–39 968
40–41 907
42–43 821
44–45 763
46–47 689
48–49 543
50–51 543
52–53 518
54–55 500
56–57 458
58–59 400
60–61 337
62–63 308
64–65 292 65
66–67 249
68–69 213
70–71 192
72–73 189
74–75 165
76–77 139
78–79 119
80–81 121
82–83 113
84–85 88
86–87 87
88–89 75
90–91 69
92–93 57
94–95 46
96–97 38
98–99 34
100–101 36
102–103 27
104–105 37
106–107 18
108–109 31
110–111 19
112–113 16
114–115 12
116–117 20
118–119 15
120–121 5
122–123 20
124–125 8
126–127 5
128–129 7
130 3
131+ 98
Download as CSV

Yaoqi Zhou D-index placement in Computer Science in 2026 - data summary

  • The chart plots the discipline H-index (D-index) of all 14,188 Computer Science scientists ranked by Research.com in 2026, grouped into 52 ranges running from 30–31 to 131+ D-Index.
  • Yaoqi Zhou, a Computer Science scholar from Griffith University, records 65 D-Index - the 83rd percentile of the discipline.
  • 83% of ranked Computer Science scientists score the same or lower than Yaoqi Zhou, and about 17% score higher.
  • The median of the discipline falls in the 44–45 D-Index range, and Yaoqi Zhou ranks above the median.
  • The most crowded range is 36–37 D-Index, holding 990 scientists (7% of the field).
  • 71% of the field sits in the lowest quarter of the value range (up to 54–55 D-Index), so the distribution is heavily right-skewed and high scores are rare.
  • The final bar has no upper bound: it groups every scientist with 131 D-Index or more, 98 scientists in all (<1% of the field).

Research.com Recognitions

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

Overview

Yaoqi Zhou is affiliated with Griffith University in Australia and has an extensive publication record primarily in the field of Biochemistry, Genetics and Molecular Biology. Their research contributions span various subfields including Molecular Biology, Geology, Infectious Diseases, Materials Chemistry, and Plant Science.

Their work frequently addresses topics related to RNA and protein synthesis mechanisms, machine learning applications in bioinformatics, genomics and phylogenetic studies, protein structure and dynamics, RNA modifications and cancer, RNA research and splicing, as well as hydrocarbon exploration and reservoir analysis.

Among their recent papers are:

  • Critical assessment of protein intrinsic disorder prediction, 2021, Nature Methods
  • Structure-aware protein-protein interaction site prediction using deep graph convolutional network, 2021, Bioinformatics
  • Improved RNA secondary structure and tertiary base-pairing prediction using evolutionary profile, mutational coupling and two-dimensional transfer learning, 2021, Bioinformatics
  • DescribePROT: database of amino acid-level protein structure and function predictions, 2020, Nucleic Acids Research
  • Multiple sequence alignment-based RNA language model and its application to structural inference, 2023, Nucleic Acids Research

Yaoqi Zhou has published extensively in several venues, with notable contributions in:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Bioinformatics
  • Nucleic Acids Research
  • Faculty Opinions - Post-Publication Peer Review of the Biomedical Literature
  • Goldschmidt Abstracts

Collaboration is a significant aspect of Zhou's research, with frequent co-authors including Jian Zhan, Thomas Litfin, Jaswinder Singh, Kuldip K. Paliwal, and Jaspreet Singh. This network reflects a multidisciplinary approach to scientific inquiry.

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

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

    Shicai Xu;Jian Zhan;Baoyuan Man;Shouzhen Jiang

  • 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

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

    Jaswinder Singh;Jack Hanson;Kuldip Paliwal;Yaoqi Zhou

  • 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

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

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

  • Protein binding site prediction using an empirical scoring function

    Shide Liang;Chi Zhang;Song Liu;Yaoqi Zhou

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

    Hongyi Zhou;Yaoqi Zhou

  • 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

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

    Yuedong Yang;Jianzhao Gao;Jihua Wang;Rhys Heffernan

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

    Hongyi Zhou;Yaoqi Zhou

  • 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

  • Folding rate prediction using total contact distance.

    Hongyi Zhou;Yaoqi Zhou

  • 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

  • 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

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

    Ofer Dor;Yaoqi Zhou

  • 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

  • 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

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

    Qianmu Yuan;Jianwen Chen;Huiying Zhao;Yaoqi Zhou

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

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

  • 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

  • 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

Frequent Co-Authors

Yuedong Yang
Yuedong Yang Sun Yat-sen University
George Stell
George Stell Stony Brook University
Chi Zhang
Chi Zhang Hohai University
Kuldip K. Paliwal
Kuldip K. Paliwal Griffith University
Matthew Mort
Matthew Mort Cardiff University
David Neil Cooper
David Neil Cooper Cardiff University
Yunlong Liu
Yunlong Liu Indiana University
Carol K. Hall
Carol K. Hall North Carolina State University
Martin Karplus
Martin Karplus Harvard University
Abdul Sattar
Abdul Sattar Griffith University

External Links

Personal website of Yaoqi Zhou

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2027 Can You Get Into an Ultrasound Technology Program with a Low GPA? Admission Chances & Workarounds
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2027 Competency-Based Online Speech Pathology Master's Degrees
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2027 How Fast Can You Get a History Degree Online?
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