Mingyao Li

33.4k total citations · 8 hit papers
172 papers, 11.2k citations indexed

About

Mingyao Li is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Mingyao Li has authored 172 papers receiving a total of 11.2k indexed citations (citations by other indexed papers that have themselves been cited), including 96 papers in Molecular Biology, 61 papers in Genetics and 27 papers in Cancer Research. Recurrent topics in Mingyao Li's work include Genetic Associations and Epidemiology (44 papers), RNA modifications and cancer (24 papers) and Single-cell and spatial transcriptomics (23 papers). Mingyao Li is often cited by papers focused on Genetic Associations and Epidemiology (44 papers), RNA modifications and cancer (24 papers) and Single-cell and spatial transcriptomics (23 papers). Mingyao Li collaborates with scholars based in United States, China and Canada. Mingyao Li's co-authors include Kai Wang, Håkon Håkonarson, Maja Bućan, Joseph Glessner, Struan F.A. Grant, Nancy R. Zhang, Katalin Suszták, Rui Liu, Dexter Hadley and Muredach P. Reilly and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Mingyao Li

169 papers receiving 11.0k citations

Hit Papers

PennCNV: An integrated hidden Markov model designed for h... 2007 2026 2013 2019 2007 2007 2010 2019 2018 250 500 750 1000
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. PennCNV: An integrated hidden Markov model designed for high-resolution copy number variation detection in whole-genome SNP genotyping data
    2007 1.2k citations Kai Wang, Mingyao Li et al. profile →
  2. Pathway-Based Approaches for Analysis of Genomewide Association Studies
    2007 668 citations Kai Wang, Mingyao Li et al. profile →
  3. Analysing biological pathways in genome-wide association studies
    2010 566 citations Kai Wang, Mingyao Li et al. profile →
  4. Bulk tissue cell type deconvolution with multi-subject single-cell expression reference
    2019 472 citations Xuran Wang, Jihwan Park et al. Nature Communications profile →
  5. SAVER: gene expression recovery for single-cell RNA sequencing
    2018 458 citations Mo Huang, Jingshu Wang et al. profile →
  6. SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network
    2021 450 citations Jian Hu, Amelia Schroeder et al. profile →
  7. Deep learning enables accurate clustering with batch effect removal in single-cell RNA-seq analysis
    2020 264 citations Yafei Lyu, Huize Pan et al. Nature Communications profile →
  8. Inferring super-resolution tissue architecture by integrating spatial transcriptomics with histology
    2024 73 citations Daiwei Zhang, Amelia Schroeder et al. Nature Biotechnology profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Mingyao Li United States 53 6.4k 3.8k 1.6k 1.2k 899 172 11.2k
Shrikant Mane United States 41 6.5k 1.0× 2.8k 0.7× 1.8k 1.1× 1.3k 1.1× 1.8k 2.0× 100 12.5k
Pauline C. Ng United States 19 7.3k 1.1× 5.2k 1.4× 1.4k 0.9× 791 0.7× 309 0.3× 23 12.5k
Soumya Raychaudhuri United States 59 7.1k 1.1× 3.1k 0.8× 1.5k 0.9× 4.5k 3.9× 707 0.8× 176 15.1k
Peter J. van der Spek Netherlands 55 7.0k 1.1× 1.4k 0.4× 1.8k 1.1× 1.0k 0.9× 287 0.3× 252 12.6k
Peter N. Robinson Germany 59 7.3k 1.1× 5.5k 1.4× 1.6k 1.0× 595 0.5× 215 0.2× 326 13.4k
Jonathan Marchini United Kingdom 34 5.7k 0.9× 10.3k 2.7× 1.1k 0.6× 819 0.7× 250 0.3× 53 17.0k
Michael Boehnke United States 64 8.3k 1.3× 8.8k 2.3× 855 0.5× 676 0.6× 550 0.6× 208 17.2k
David Valle United States 60 10.0k 1.6× 2.7k 0.7× 1.6k 1.0× 693 0.6× 327 0.4× 226 14.4k
Jiang Qian United States 61 7.9k 1.2× 880 0.2× 1.2k 0.7× 805 0.7× 639 0.7× 300 12.4k
Kevin G. Becker United States 71 10.8k 1.7× 2.0k 0.5× 3.4k 2.1× 2.4k 2.1× 301 0.3× 293 18.5k

Countries citing papers authored by Mingyao Li

Since Specialization
Citations

This map shows the geographic impact of Mingyao Li'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 Mingyao Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingyao Li more than expected).

Fields of papers citing papers by Mingyao Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mingyao Li. 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 Mingyao Li. The network helps show where Mingyao Li may publish in the future.

Co-authorship network of co-authors of Mingyao Li

This figure shows the co-authorship network connecting the top 25 collaborators of Mingyao Li. A scholar is included among the top collaborators of Mingyao Li 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 Mingyao Li. Mingyao Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Bashore, Alexander C., Hanying Yan, Chenyi Xue, et al.. (2024). High-Dimensional Single-Cell Multimodal Landscape of Human Carotid Atherosclerosis. Arteriosclerosis Thrombosis and Vascular Biology. 44(4). 930–945. 35 indexed citations
2.
Bashore, Alexander C., Chenyi Xue, Eunyoung Kim, et al.. (2024). Monocyte Single-Cell Multimodal Profiling in Cardiovascular Disease Risk States. Circulation Research. 135(6). 685–700. 9 indexed citations
3.
Wang, Linghua, Mingyao Li, & Tae Hyun Hwang. (2024). The 3D Revolution in Cancer Discovery. Cancer Discovery. 14(4). 625–629. 10 indexed citations
4.
Zhang, Daiwei, Amelia Schroeder, Hanying Yan, et al.. (2024). Inferring super-resolution tissue architecture by integrating spatial transcriptomics with histology. Nature Biotechnology. 42(9). 1372–1377. 73 indexed citations breakdown →
5.
Fan, Jiaxin, et al.. (2022). MuSiC2: cell-type deconvolution for multi-condition bulk RNA-seq data. Briefings in Bioinformatics. 23(6). 24 indexed citations
6.
Cynn, Esther, Daniel Y. Li, M. O'Reilly, et al.. (2022). Human Macrophage Long Intergenic Noncoding RNA, SIMALR , Suppresses Inflammatory Macrophage Apoptosis via NTN1 (Netrin-1). Arteriosclerosis Thrombosis and Vascular Biology. 43(2). 286–299. 8 indexed citations
7.
Hordeaux, Juliette, Elizabeth L. Buza, Chunjuan Song, et al.. (2020). MicroRNA-mediated inhibition of transgene expression reduces dorsal root ganglion toxicity by AAV vectors in primates. Science Translational Medicine. 12(569). 107 indexed citations
8.
Liu, Esther, Byung Ha Chung, Dan Yi, et al.. (2020). Profiling APOL1 Nephropathy Risk Variants in Genome-Edited Kidney Organoids with Single-Cell Transcriptomics. Kidney360. 1(3). 203–215. 25 indexed citations
9.
Xie, Gangcai, Chengliang Dong, Yinfei Kong, et al.. (2019). Group Lasso Regularized Deep Learning for Cancer Prognosis from Multi-Omics and Clinical Features. Genes. 10(3). 240–240. 72 indexed citations
10.
Wang, Xuran, Jihwan Park, Katalin Suszták, Nancy R. Zhang, & Mingyao Li. (2019). Bulk tissue cell type deconvolution with multi-subject single-cell expression reference. Nature Communications. 10(1). 380–380. 472 indexed citations breakdown →
11.
Li, Fang, Charlly Kao, Michael V. Gonzalez, et al.. (2019). LinkedSV for detection of mosaic structural variants from linked-read exome and genome sequencing data. Nature Communications. 10(1). 5585–5585. 27 indexed citations
12.
Fu, Junling, Yonghui Wang, Ge Li, et al.. (2019). Childhood sleep duration modifies the polygenic risk for obesity in youth through leptin pathway: the Beijing Child and Adolescent Metabolic Syndrome cohort study. International Journal of Obesity. 43(8). 1556–1567. 34 indexed citations
13.
Wang, Jingshu, Mo Huang, Eduardo A. Torre, et al.. (2018). Gene expression distribution deconvolution in single-cell RNA sequencing. Proceedings of the National Academy of Sciences. 115(28). E6437–E6446. 63 indexed citations
14.
Li, Ge, Dan Feng, Yonghui Wang, et al.. (2018). Loss of Cardio-Protective Effects at the CDH13 Locus Due to Gene-Sleep Interaction: The BCAMS Study. EBioMedicine. 32. 164–171. 8 indexed citations
15.
Meyer, Nuala J., Jane F. Ferguson, Rui Feng, et al.. (2014). A Functional Synonymous Coding Variant in the IL1RN Gene Is Associated with Survival in Septic Shock. American Journal of Respiratory and Critical Care Medicine. 190(6). 656–664. 33 indexed citations
16.
Meyer, Nuala J., Rui Feng, Mingyao Li, et al.. (2013). IL1RN Coding Variant Is Associated with Lower Risk of Acute Respiratory Distress Syndrome and Increased Plasma IL-1 Receptor Antagonist. American Journal of Respiratory and Critical Care Medicine. 187(9). 950–959. 49 indexed citations
17.
18.
Li, Mingyao, Isabel X. Wang, Yun Li, et al.. (2011). Widespread RNA and DNA Sequence Differences in the Human Transcriptome. Science. 333(6038). 53–58. 342 indexed citations
19.
Zhao, Jianhua, Mingyao Li, Jonathan P. Bradfield, et al.. (2010). The role of height-associated loci identified in genome wide association studies in the determination of pediatric stature. BMC Medical Genetics. 11(1). 96–96. 46 indexed citations
20.
Li, Xiaolin, Jieqing Zhu, Rongrong Lu, et al.. (2004). The source identification and apportionment of aerosol particles in the atmosphere by scanning nuclear microprobes. Nuclear Techniques. 27(1). 27–34. 1 indexed citations

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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