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Cheng Li

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Genetics 84 1330 1259 28 27 227 66652

Cheng Li publications per year

The chart shows the history of publications by Cheng Li between 2000 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Cheng Li published across 26 years, from 2000 to 2025, averaging 15.7 papers a year. Output peaked at 58 publications in 2023. 65 of the 407 publications appeared in the last two years.

No. of publications
10 20 30 40 50
Bar chart. Horizontal axis: year, 2000 to 2025. Vertical axis: number of publications, 0 to 58. Peak 58 publications in 2023. 2000: 1 publication 2001: 6 publications 2002: 2 publications 2003: 6 publications 2004: 22 publications 2005: 19 publications 2006: 7 publications 2007: 12 publications 2008: 13 publications 2009: 15 publications 2010: 10 publications 2011: 15 publications 2012: 13 publications 2013: 11 publications 2014: 4 publications 2015: 2 publications 2016: 4 publications 2017: 12 publications 2018: 8 publications 2019: 16 publications 2020: 19 publications 2021: 21 publications 2022: 46 publications 2023: 58 publications 2024: 28 publications 2025: 37 publications
2000 2025

407 publications in total across all disciplines

View publications per year as a table
Cheng Li: publications per year, 2000 to 2025
Year Publications
2000 1
2001 6
2002 2
2003 6
2004 22
2005 19
2006 7
2007 12
2008 13
2009 15
2010 10
2011 15
2012 13
2013 11
2014 4
2015 2
2016 4
2017 12
2018 8
2019 16
2020 19
2021 21
2022 46
2023 58
2024 28
2025 37
Total 407
Download as CSV

Cheng Li publications per year - data summary

  • Cheng Li, a Genetics scholar from Peking University, has 407 publications recorded across 26 years, from 2000 to 2025.
  • The oldest publication on record dates to 2000 and the most recent to 2025.
  • The most productive year is 2023, with 58 publications.
  • The least productive year with any output is 2000, with 1 publication.
  • The rate of publication averages 15.7 papers per year over the whole span, or 15.7 per year counting only the 26 years with at least one publication.
  • The last 5 years on the chart (2021-2025) hold 190 publications, 47% of the career total.
  • Split into equal eras - 2000-2008: 88 publications (9.8 per year); 2009-2017: 86 publications (9.6 per year); 2018-2025: 233 publications (29.1 per year).
  • Comparing the opening and closing eras, the overall trend of publication is rising.

Cheng Li 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 Cheng Li sits on this spectrum.

No. of scientists
50 100 150 200
Bar chart with 67 bars. Horizontal axis: publications, 45–54 to 703+. Vertical axis: number of scientists, 0 to 217. Most scientists, 217, have 125–134 publications. The last bar groups every scientist with 703 publications or more. The highlighted bar, 225–234 publications, is where this scientist sits. 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
45–54 publications 703+

This scientist: 227 publications — 60th percentile

60% of scientists in this discipline score the same or lower.

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

View publications distribution as a table
Number of Genetics scientists by publication count, Research.com 2026 ranking edition. Based on 4,342 ranked scientists.
Publications Scientists This scientist
45–54 6
55–64 10
65–74 35
75–84 84
85–94 102
95–104 151
105–114 175
115–124 203
125–134 217
135–144 205
145–154 193
155–164 188
165–174 170
175–184 178
185–194 164
195–204 173
205–214 159
215–224 134
225–234 143 227
235–244 105
245–254 114
255–264 92
265–274 88
275–284 87
285–294 80
295–304 62
305–314 75
315–324 67
325–334 60
335–344 52
345–354 40
355–364 48
365–374 47
375–384 46
385–394 31
395–404 27
405–414 40
415–424 30
425–434 43
435–444 29
445–454 14
455–464 28
465–474 21
475–484 21
485–494 22
495–504 17
505–514 12
515–524 11
525–534 8
535–544 8
545–554 14
555–564 4
565–574 11
575–584 5
585–594 11
595–604 12
605–614 7
615–624 6
625–634 10
635–644 9
645–654 10
655–664 6
665–674 6
675–684 6
685–694 4
695–702 6
703+ 100
Download as CSV

Cheng Li publication distribution in Genetics in 2026 - data summary

  • The chart plots the publication count of all 4,342 Genetics scientists ranked by Research.com in 2026, grouped into 67 ranges running from 45–54 to 703+ publications.
  • Cheng Li, a Genetics scholar from Peking University, records 227 publications - the 60th percentile of the discipline.
  • 60% of ranked Genetics scientists score the same or lower than Cheng Li, and about 40% score higher.
  • The median of the discipline falls in the 195–204 publications range, and Cheng Li ranks above the median.
  • The most crowded range is 125–134 publications, holding 217 scientists (5% of the field).
  • 56% of the field sits in the lowest quarter of the value range (up to 205–214 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 703 publications or more, 100 scientists in all (2% of the field).

Cheng Li 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 Cheng Li sits on this spectrum.

No. of scientists
50 100 150
Bar chart with 61 bars. Horizontal axis: D-Index, 40–41 to 160+. Vertical axis: number of scientists, 0 to 191. Most scientists, 191, have 62–63 D-Index. The last bar groups every scientist with 160 D-Index or more. The highlighted bar, 84–85 D-Index, is where this scientist sits. 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
40–41 D-Index 160+

This scientist: 84 D-Index — 69th percentile

69% of scientists in this discipline score the same or lower.

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

View D-Index distribution as a table
Number of Genetics scientists by D-index, Research.com 2026 ranking edition. Based on 4,342 ranked scientists.
D-Index Scientists This scientist
40–41 24
42–43 52
44–45 84
46–47 112
48–49 118
50–51 141
52–53 143
54–55 145
56–57 179
58–59 162
60–61 175
62–63 191
64–65 172
66–67 184
68–69 164
70–71 158
72–73 150
74–75 136
76–77 127
78–79 127
80–81 111
82–83 110
84–85 110 84
86–87 84
88–89 102
90–91 66
92–93 72
94–95 70
96–97 54
98–99 60
100–101 49
102–103 55
104–105 45
106–107 42
108–109 28
110–111 39
112–113 25
114–115 31
116–117 29
118–119 34
120–121 29
122–123 29
124–125 18
126–127 27
128–129 22
130–131 16
132–133 11
134–135 17
136–137 12
138–139 21
140–141 4
142–143 9
144–145 14
146–147 6
148–149 10
150–151 7
152–153 9
154–155 8
156–157 8
158–159 9
160+ 96
Download as CSV

Cheng Li D-index placement in Genetics in 2026 - data summary

  • The chart plots the discipline H-index (D-index) of all 4,342 Genetics scientists ranked by Research.com in 2026, grouped into 61 ranges running from 40–41 to 160+ D-Index.
  • Cheng Li, a Genetics scholar from Peking University, records 84 D-Index - the 69th percentile of the discipline.
  • 69% of ranked Genetics scientists score the same or lower than Cheng Li, and about 31% score higher.
  • The median of the discipline falls in the 70–71 D-Index range, and Cheng Li ranks above the median.
  • The most crowded range is 62–63 D-Index, holding 191 scientists (4% of the field).
  • 51% of the field sits in the lowest quarter of the value range (up to 70–71 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 160 D-Index or more, 96 scientists in all (2% of the field).

Overview

Cheng Li is affiliated with Peking University in China, focusing research primarily in the fields of Biochemistry, Genetics and Molecular Biology, and Medicine. Their work spans several specialized subfields, including Molecular Biology, Immunology, Cancer Research, Oncology, and Pulmonary and Respiratory Medicine. This interdisciplinary approach supports research into complex biological mechanisms across health and disease contexts.

The scientist's research addresses a variety of main topics such as Genomics and Chromatin Dynamics, RNA Research and Splicing, Pluripotent Stem Cells Research, CRISPR and Genetic Engineering, RNA modifications and cancer, Cancer-related molecular mechanisms research, and Single-cell and spatial transcriptomics. These topics reflect a significant focus on the molecular and genetic regulatory systems influencing cellular function and pathology.

Cheng Li has contributed to numerous publications in notable venues, including:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Cell Research
  • Cell Reports
  • Cell stem cell
  • Nature Communications

Selected papers showcasing their recent work include:

  • "Single-cell transcriptome profiling reveals neutrophil heterogeneity in homeostasis and infection," published in 2020 in Nature Immunology
  • "Elimination of senescent cells by β-galactosidase-targeted prodrug attenuates inflammation and restores physical function in aged mice," published in 2020 in Cell Research
  • "Chemical reprogramming of human somatic cells to pluripotent stem cells," published in 2022 in Nature
  • "Potent binding of 2019 novel coronavirus spike protein by a SARS coronavirus-specific human monoclonal antibody," published in 2020 in bioRxiv (Cold Spring Harbor Laboratory)
  • "Genome-wide analyses of chromatin interactions after the loss of Pol I, Pol II, and Pol III," published in 2020 in Genome Biology

Frequent collaborators include:

  • Hongkui Deng
  • Yujie Sun
  • Yingping Hou
  • Jingyang Guan
  • Yulin Lyu

This network of coauthors suggests active involvement in collaborative research projects integrating various molecular and cellular biology disciplines.

Best Publications

  • Bioconductor: open software development for computational biology and bioinformatics

    Robert C Gentleman;Vincent J Carey;Douglas M. Bates;B.M. Bolstad

  • GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses.

    Zefang Tang;Chenwei Li;Boxi Kang;Ge Gao

  • Adjusting batch effects in microarray expression data using empirical Bayes methods

    W. Evan Johnson;Cheng Li;Ariel Rabinovic

  • Model-based analysis of oligonucleotide arrays: Expression index computation and outlier detection

    Cheng Li;Wing Hung Wong

  • Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses

    Arindam Bhattacharjee;William G. Richards;Jane Staunton;Cheng Li

  • Gene regulation and DNA damage in the ageing human brain.

    Tao Lu;Ying Pan;Shyan Yuan Kao;Cheng Li

  • Integrative genomic analyses identify MITF as a lineage survival oncogene amplified in malignant melanoma

    Levi A. Garraway;Hans R. Widlund;Mark A. Rubin;Gad Getz

  • Genome-wide expression analysis reveals dysregulation of myelination-related genes in chronic schizophrenia.

    Yaron Hakak;John R. Walker;Cheng Li;Wing Hung Wong

  • Model-based analysis of oligonucleotide arrays: model validation, design issues and standard error application

    Cheng Li;Wing Hung Wong

  • Single-cell transcriptome profiling reveals neutrophil heterogeneity in homeostasis and infection

    Xuemei Xie;Qiang Shi;Peng Wu;Xiaoyu Zhang

  • An Integrated View of Copy Number and Allelic Alterations in the Cancer Genome Using Single Nucleotide Polymorphism Arrays

    Xiaojun Zhao;Cheng Li;J. Guillermo Paez;Koei Chin

  • Genome-wide analysis reveals mechanisms modulating autophagy in normal brain aging and in Alzheimer's disease

    Marta M. Lipinski;Bin Zheng;Tao Lu;Zhenyu Yan

  • Highly parallel identification of essential genes in cancer cells

    Biao Luo;Hiu Wing Cheung;Aravind Subramanian;Tanaz Sharifnia

  • Two supervised learning approaches for name disambiguation in author citations

    Hui Han;Lee Giles;Hongyuan Zha;Cheng Li

  • Feature extraction and normalization algorithms for high-density oligonucleotide gene expression array data

    Cheng Li;Wing Hung Wong

  • dChipSNP: significance curve and clustering of SNP-array-based loss-of-heterozygosity data

    Ming Lin;Lee-Jen Wei;William R. Sellers;Marshall Lieberfarb

  • Derivation of Pluripotent Stem Cells with In Vivo Embryonic and Extraembryonic Potency

    Yang Yang;Bei Liu;Jun Xu;Jinlin Wang

  • Genome coverage and sequence fidelity of ϕ29 polymerase‐based multiple strand displacement whole genome amplification

    J. Guillermo Paez;Ming Lin;Rameen Beroukhim;Jeffrey C. Lee

  • CRISPR-Edited Stem Cells in a Patient with HIV and Acute Lymphocytic Leukemia

    Lei Xu;Jun Wang;Yulin Liu;Liangfu Xie

  • Homozygous Deletions and Chromosome Amplifications in Human Lung Carcinomas Revealed by Single Nucleotide Polymorphism Array Analysis

    Xiaojun Zhao;Barbara A. Weir;Thomas Louis LaFramboise;Ming Lin

Frequent Co-Authors

Nikhil C. Munshi
Nikhil C. Munshi Harvard University
Hervé Avet-Loiseau
Hervé Avet-Loiseau Inserm
Wing Hung Wong
Wing Hung Wong Stanford University
Matthew Meyerson
Matthew Meyerson Harvard University
Kenneth C. Anderson
Kenneth C. Anderson Harvard University
Yu-Tzu Tai
Yu-Tzu Tai Harvard University
Rameen Beroukhim
Rameen Beroukhim Harvard University
William R. Sellers
William R. Sellers Harvard University
Hongkui Deng
Hongkui Deng Peking University
Faith E. Davies
Faith E. Davies New York University Langone Medical Center

External Links

Personal website of Cheng Li

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Related Online Degrees & Career Pathways

Genetics opens the door to a variety of fulfilling career pathways in healthcare and research. Many professionals interested in genetics choose to start with foundational healthcare roles, such as becoming a medical assistant through medical assistant training. This path offers accelerated programs that enable students to quickly enter the workforce and gain hands-on experience with lab work and patient interaction.

For those seeking to advance their nursing education, there are flexible options like rn to bsn no clinical hours programs. These online degrees make it easier for working nurses to build genetics knowledge without the requirement of extra clinical assignments.

Professionals aiming for leadership or advanced clinical roles might consider graduate programs, such as the shortest dnp program or an dnp online pathway. These programs prioritize flexibility and speed, making it easier for working adults to specialize and move into high-impact jobs in genetics, research, or healthcare administration.

Best Scientists Citing Cheng Li

Nikhil C. Munshi

Nikhil C. Munshi

Harvard University

Publications: 136

Kenneth C. Anderson

Kenneth C. Anderson

Harvard University

Publications: 135

Matthew Meyerson

Matthew Meyerson

Harvard University

Publications: 123

William C. Hahn

William C. Hahn

Dana-Farber Cancer Institute

Publications: 114

Levi A. Garraway

Levi A. Garraway

Roche (United States)

Publications: 93

Todd R. Golub

Todd R. Golub

Harvard University

Publications: 78

Rameen Beroukhim

Rameen Beroukhim

Harvard University

Publications: 76

Eric S. Lander

Eric S. Lander

Broad Institute

Publications: 75

Vahram Haroutunian

Vahram Haroutunian

Icahn School of Medicine at Mount Sinai

Publications: 70

Daniel H. Geschwind

Daniel H. Geschwind

University of California, Los Angeles

Publications: 67

Terence P. Speed

Terence P. Speed

Walter and Eliza Hall Institute of Medical Research

Publications: 64

Teru Hideshima

Teru Hideshima

Harvard University

Publications: 64

Gareth J. Morgan

Gareth J. Morgan

Boston University

Publications: 64

Paul C. Boutros

Paul C. Boutros

University of California, Los Angeles

Publications: 62

David E. Fisher

David E. Fisher

Harvard University

Publications: 62

Aviv Regev

Aviv Regev

Genentech

Publications: 61

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Adam S. Foster

Adam S. Foster

Aalto University

S. M. Yusuf

S. M. Yusuf

Bhabha Atomic Research Centre

Tracy Langkilde

Tracy Langkilde

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Fengtang Yang

Fengtang Yang

Wellcome Sanger Institute

Diane M. Citron

Diane M. Citron

Michigan State University

Graeme E. Batley

Graeme E. Batley

Commonwealth Scientific and Industrial Research Organisation

R.D.G. Theakston

R.D.G. Theakston

Liverpool School of Tropical Medicine

Carlo C. Maley

Carlo C. Maley

Arizona State University

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Jacques Boulègue

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