World's Best Scientists 2026 revealed!

D-Index & Metrics

Genetics

D-Index
63
Citations
48038
World Ranking
2821
National Ranking
1234

Haiyuan Yu publication distribution in Genetics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Genetics in 2026. The highlighted bar marks where Haiyuan Yu sits on this spectrum.

45–54 publications: 6 scientists 55–64 publications: 10 scientists 65–74 publications: 35 scientists 75–84 publications: 84 scientists 85–94 publications: 102 scientists 95–104 publications: 151 scientists 105–114 publications: 175 scientists 115–124 publications: 203 scientists 125–134 publications: 217 scientists 135–144 publications: 205 scientists 145–154 publications: 193 scientists 155–164 publications: 188 scientists 165–174 publications: 170 scientists 175–184 publications: 178 scientists 185–194 publications: 164 scientists 195–204 publications: 173 scientists 205–214 publications: 159 scientists 215–224 publications: 134 scientists 225–234 publications: 143 scientists 235–244 publications: 105 scientists 245–254 publications: 114 scientists 255–264 publications: 92 scientists 265–274 publications: 88 scientists 275–284 publications: 87 scientists 285–294 publications: 80 scientists 295–304 publications: 62 scientists 305–314 publications: 75 scientists 315–324 publications: 67 scientists 325–334 publications: 60 scientists 335–344 publications: 52 scientists 345–354 publications: 40 scientists 355–364 publications: 48 scientists 365–374 publications: 47 scientists 375–384 publications: 46 scientists 385–394 publications: 31 scientists 395–404 publications: 27 scientists 405–414 publications: 40 scientists 415–424 publications: 30 scientists 425–434 publications: 43 scientists 435–444 publications: 29 scientists 445–454 publications: 14 scientists 455–464 publications: 28 scientists 465–474 publications: 21 scientists 475–484 publications: 21 scientists 485–494 publications: 22 scientists 495–504 publications: 17 scientists 505–514 publications: 12 scientists 515–524 publications: 11 scientists 525–534 publications: 8 scientists 535–544 publications: 8 scientists 545–554 publications: 14 scientists 555–564 publications: 4 scientists 565–574 publications: 11 scientists 575–584 publications: 5 scientists 585–594 publications: 11 scientists 595–604 publications: 12 scientists 605–614 publications: 7 scientists 615–624 publications: 6 scientists 625–634 publications: 10 scientists 635–644 publications: 9 scientists 645–654 publications: 10 scientists 655–664 publications: 6 scientists 665–674 publications: 6 scientists 675–684 publications: 6 scientists 685–694 publications: 4 scientists 695–702 publications: 6 scientists 703+ publications: 100 scientists
45 publications 703+

This scientist: 148 publications — 29th percentile

29% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 703 publications or more.

Haiyuan Yu D-index placement in Genetics in 2026

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

40–41 D-Index: 24 scientists 42–43 D-Index: 52 scientists 44–45 D-Index: 84 scientists 46–47 D-Index: 112 scientists 48–49 D-Index: 118 scientists 50–51 D-Index: 141 scientists 52–53 D-Index: 143 scientists 54–55 D-Index: 145 scientists 56–57 D-Index: 179 scientists 58–59 D-Index: 162 scientists 60–61 D-Index: 175 scientists 62–63 D-Index: 191 scientists 64–65 D-Index: 172 scientists 66–67 D-Index: 184 scientists 68–69 D-Index: 164 scientists 70–71 D-Index: 158 scientists 72–73 D-Index: 150 scientists 74–75 D-Index: 136 scientists 76–77 D-Index: 127 scientists 78–79 D-Index: 127 scientists 80–81 D-Index: 111 scientists 82–83 D-Index: 110 scientists 84–85 D-Index: 110 scientists 86–87 D-Index: 84 scientists 88–89 D-Index: 102 scientists 90–91 D-Index: 66 scientists 92–93 D-Index: 72 scientists 94–95 D-Index: 70 scientists 96–97 D-Index: 54 scientists 98–99 D-Index: 60 scientists 100–101 D-Index: 49 scientists 102–103 D-Index: 55 scientists 104–105 D-Index: 45 scientists 106–107 D-Index: 42 scientists 108–109 D-Index: 28 scientists 110–111 D-Index: 39 scientists 112–113 D-Index: 25 scientists 114–115 D-Index: 31 scientists 116–117 D-Index: 29 scientists 118–119 D-Index: 34 scientists 120–121 D-Index: 29 scientists 122–123 D-Index: 29 scientists 124–125 D-Index: 18 scientists 126–127 D-Index: 27 scientists 128–129 D-Index: 22 scientists 130–131 D-Index: 16 scientists 132–133 D-Index: 11 scientists 134–135 D-Index: 17 scientists 136–137 D-Index: 12 scientists 138–139 D-Index: 21 scientists 140–141 D-Index: 4 scientists 142–143 D-Index: 9 scientists 144–145 D-Index: 14 scientists 146–147 D-Index: 6 scientists 148–149 D-Index: 10 scientists 150–151 D-Index: 7 scientists 152–153 D-Index: 9 scientists 154–155 D-Index: 8 scientists 156–157 D-Index: 8 scientists 158–159 D-Index: 9 scientists 160+ D-Index: 96 scientists
40 D-Index 160+

This scientist: 63 D-Index — 35th percentile

35% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 160 D-Index or more.

Overview

Haiyuan Yu is affiliated with Cornell University in the United States and has a substantial publication record in the fields of biochemistry, genetics, and molecular biology. Their work spans a variety of subfields including molecular biology, materials chemistry, genetics, neurology, and aerospace engineering.

Their research covers numerous specialized topics, among which are:

  • Bioinformatics and genomic networks
  • High-temperature coating behaviors
  • Genomics and chromatin dynamics
  • RNA research and splicing
  • RNA and protein synthesis mechanisms
  • Computational drug discovery methods
  • Protein structure and dynamics

Haiyuan Yu has contributed to many publications, frequently appearing in the following venues:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Nature Biotechnology
  • Surface and Coatings Technology
  • Nature Communications
  • Physical Review A

The scientist has coauthored multiple papers with several researchers, including:

  • Shayne D. Wierbowski
  • Alden King-Yung Leung
  • Robert Fragoza
  • John T. Lis
  • Kumar Yugandhar

Among the recent papers authored or coauthored by Haiyuan Yu are:

  • "A comprehensive SARS-CoV-2-human protein-protein interactome reveals COVID-19 pathobiology and potential host therapeutic targets" (2022, Nature Biotechnology)
  • "In-depth and 3-dimensional exploration of the budding yeast phosphoproteome" (2021, EMBO Reports)
  • "Network medicine links SARS-CoV-2/COVID-19 infection to brain microvascular injury and neuroinflammation in dementia-like cognitive impairment" (2021, Alzheimer's Research & Therapy)
  • "SAAMBE-3D: Predicting Effect of Mutations on Protein-Protein Interactions" (2020, International Journal of Molecular Sciences)
  • "Loss of TMEM 106B and PGRN leads to severe lysosomal abnormalities and neurodegeneration in mice" (2020, EMBO Reports)

Best Publications

  • A global reference for human genetic variation.

    Adam Auton;Gonçalo R. Abecasis;David M. Altshuler;Richard M. Durbin

  • Global landscape of protein complexes in the yeast Saccharomyces cerevisiae

    Nevan J. Krogan;Gerard Cagney;Gerard Cagney;Haiyuan Yu;Gouqing Zhong

  • A Map of the Interactome Network of the Metazoan C. elegans

    Siming Li;Christopher M. Armstrong;Nicolas Bertin;Hui Ge

  • High-Quality Binary Protein Interaction Map of the Yeast Interactome Network

    Haiyuan Yu;Pascal Braun;Muhammed A Yildirim;Irma Lemmens

  • A Bayesian networks approach for predicting protein-protein interactions from genomic data.

    Ronald Jansen;Haiyuan Yu;Dov Greenbaum;Yuval Kluger

  • Detecting overlapping protein complexes in protein-protein interaction networks

    Tamás Nepusz;Haiyuan Yu;Alberto Paccanaro

  • Genomic analysis of regulatory network dynamics reveals large topological changes

    Nicholas M. Luscombe;M. Madan Babu;Haiyuan Yu;Michael Snyder

  • The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics.

    Haiyuan Yu;Philip M Kim;Emmett Sprecher;Valery Trifonov

  • An empirical framework for binary interactome mapping

    Kavitha Venkatesan;Kavitha Venkatesan;Jean François Rual;Alexei Vazquez;Alexei Vazquez;Ulrich Stelzl

  • A global reference for human genetic variation

    Adam Auton;Gonçalo R. Abecasis;David M. Altshuler;Richard M. Durbin

  • Annotation Transfer Between Genomes: Protein–Protein Interologs and Protein–DNA Regulogs

    Haiyuan Yu;Nicholas M. Luscombe;Hao Xin Lu;Xiaowei Zhu

  • Biochemical and genetic analysis of the yeast proteome with a movable ORF collection

    Daniel M. Gelperin;Michael A. White;Martha L. Wilkinson;Yoshiko Kon

  • An experimentally derived confidence score for binary protein-protein interactions

    Pascal Braun;Murat Tasan;Matija Dreze;Matija Dreze;Miriam Barrios-Rodiles

  • HINT: High-quality protein interactomes and their applications in understanding human disease

    Jishnu Das;Haiyuan Yu

  • Three-dimensional reconstruction of protein networks provides insight into human genetic disease.

    Xiujuan Wang;Xiaomu Wei;Xiaomu Wei;Bram Thijssen;Jishnu Das

  • Divergence of transcription factor binding sites across related yeast species

    Anthony R. Borneman;Tara A. Gianoulis;Zhengdong D. Zhang;Haiyuan Yu

  • Integrative Annotation of Variants from 1092 Humans: Application to Cancer Genomics

    Ekta Khurana;Yao Fu;Vincenza Colonna;Vincenza Colonna;Xinmeng Jasmine Mu

  • Edgetic perturbation models of human inherited disorders.

    Quan Zhong;Nicolas Simonis;Qian -Ru Li;Benoît Charloteaux;Benoît Charloteaux

  • Genomic analysis of the hierarchical structure of regulatory networks

    Haiyuan Yu;Mark Gerstein

  • Genomic analysis of essentiality within protein networks.

    Haiyuan Yu;Dov Greenbaum;Hao Xin Lu;Xiaowei Zhu

Frequent Co-Authors

Mark Gerstein
Mark Gerstein Yale University
Marc Vidal
Marc Vidal Harvard University
Frederick P. Roth
Frederick P. Roth Lunenfeld-Tanenbaum Research Institute
David E. Hill
David E. Hill Harvard University
Steven M. Lipkin
Steven M. Lipkin Weill Cornell Medicine
Michael Snyder
Michael Snyder Stanford University
Marcus B. Smolka
Marcus B. Smolka Cornell University
Kasper Lage
Kasper Lage Harvard University
Tuuli Lappalainen
Tuuli Lappalainen Royal Institute of Technology
Peter D. Stenson
Peter D. Stenson Cardiff University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

For students intrigued by genetics, several online degrees and healthcare career pathways complement this field. Many genetics graduates pursue clinical roles, research, or further education in allied health professions. Advancements in online education make these paths more accessible and flexible, especially for working professionals or those seeking career transitions.

Exploring nurse practitioner courses online can open doors to advanced practice roles that integrate genetic counseling and personalized medicine. Those interested in fast-tracking their careers might consider the cheapest accelerated nursing programs, offering a quick path to licensure and professional growth.

For registered nurses seeking to further specialize, there are flexible and affordable bridge programs such as msn to dnp programs, paving the way for leadership positions and advanced clinical practice. Additionally, transitioning from an RN to a bachelor’s degree is made cost-effective through affordable rn to bsn pathways.

These online degree options help build strong foundational knowledge and skills, providing diverse career opportunities intersecting with genetics and healthcare innovation.

Best Scientists Citing Haiyuan Yu

Trending Scientists

Recently Published Articles