Qunhua Li

7.1k total citations
35 papers, 997 citations indexed

About

Qunhua Li is a scholar working on Molecular Biology, Genetics and Statistics and Probability. According to data from OpenAlex, Qunhua Li has authored 35 papers receiving a total of 997 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Molecular Biology, 7 papers in Genetics and 5 papers in Statistics and Probability. Recurrent topics in Qunhua Li's work include Genomics and Chromatin Dynamics (10 papers), Gene expression and cancer classification (6 papers) and Single-cell and spatial transcriptomics (5 papers). Qunhua Li is often cited by papers focused on Genomics and Chromatin Dynamics (10 papers), Gene expression and cancer classification (6 papers) and Single-cell and spatial transcriptomics (5 papers). Qunhua Li collaborates with scholars based in United States, China and Sweden. Qunhua Li's co-authors include Feipeng Zhang, Tao Yang, Ross C. Hardison, Feng Yue, William Stafford Noble, Fan Song, Galip Gürkan Yardımcı, Tao Liu, Paweł Krajewski and István Ladunga and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Journal of the American Statistical Association.

In The Last Decade

Qunhua Li

31 papers receiving 984 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Qunhua Li United States 14 791 184 129 85 51 35 997
Kun Liang China 19 429 0.5× 386 2.1× 106 0.8× 41 0.5× 46 0.9× 42 1.0k
Stefan Platz United Kingdom 9 377 0.5× 53 0.3× 75 0.6× 43 0.5× 20 0.4× 14 707
Robert Bjornson United States 16 1000 1.3× 114 0.6× 250 1.9× 152 1.8× 5 0.1× 23 1.4k
Maria Keays United Kingdom 5 457 0.6× 77 0.4× 65 0.5× 82 1.0× 4 0.1× 5 617
Cath Brooksbank United Kingdom 18 730 0.9× 56 0.3× 75 0.6× 56 0.7× 4 0.1× 61 953
Adriano Barbosa-Silva Germany 15 473 0.6× 70 0.4× 127 1.0× 29 0.3× 8 0.2× 26 708
E Schmidt Germany 13 760 1.0× 144 0.8× 131 1.0× 73 0.9× 4 0.1× 43 1.0k
Nathalie Malo Canada 7 485 0.6× 24 0.1× 107 0.8× 39 0.5× 52 1.0× 7 797
Xosé M. Fernández United Kingdom 19 637 0.8× 59 0.3× 203 1.6× 74 0.9× 5 0.1× 41 1.0k
Shantao Li United States 12 397 0.5× 63 0.3× 140 1.1× 116 1.4× 7 0.1× 14 610

Countries citing papers authored by Qunhua Li

Since Specialization
Citations

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

Fields of papers citing papers by Qunhua Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qunhua Li

This figure shows the co-authorship network connecting the top 25 collaborators of Qunhua Li. A scholar is included among the top collaborators of Qunhua 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 Qunhua Li. Qunhua 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.
2.
McGuire, Daniel, Havell Markus, Lina Yang, et al.. (2024). Dissecting heritability, environmental risk, and air pollution causal effects using > 50 million individuals in MarketScan. Nature Communications. 15(1). 5357–5357. 3 indexed citations
3.
Li, Qunhua, et al.. (2023). RCFGL: Rapid Condition adaptive Fused Graphical Lasso and application to modeling brain region co-expression networks. PLoS Computational Biology. 19(1). e1010758–e1010758. 4 indexed citations
4.
5.
Yang, Tao, et al.. (2021). Methods to Assess the Reproducibility and Similarity of Hi-C Data. Methods in molecular biology. 2301. 17–37. 2 indexed citations
6.
Chai, Zhi, Yafei Lyu, Qiuyan Chen, et al.. (2021). RNAseq studies reveal distinct transcriptional response to vitamin A deficiency in small intestine versus colon, uncovering novel vitamin A-regulated genes. The Journal of Nutritional Biochemistry. 98. 108814–108814. 5 indexed citations
7.
Xiang, Guanjue, Cheryl A. Keller, Belinda Giardine, et al.. (2020). S3norm: simultaneous normalization of sequencing depth and signal-to-noise ratio in epigenomic data. Nucleic Acids Research. 48(8). e43–e43. 19 indexed citations
8.
An, Lin, Tao Yang, Jiahao Yang, et al.. (2019). OnTAD: hierarchical domain structure reveals the divergence of activity among TADs and boundaries. Genome biology. 20(1). 282–282. 47 indexed citations
9.
Lyu, Yafei, Lingzhou Xue, Feipeng Zhang, et al.. (2018). Condition-adaptive fused graphical lasso (CFGL): An adaptive procedure for inferring condition-specific gene co-expression network. PLoS Computational Biology. 14(9). e1006436–e1006436. 17 indexed citations
10.
Starenki, Dmytro, et al.. (2018). powerTCR: A model-based approach to comparative analysis of the clone size distribution of the T cell receptor repertoire. PLoS Computational Biology. 14(11). e1006571–e1006571. 13 indexed citations
11.
Reddivari, Lavanya, Sridhar Radhakrishnan, Xia Xiao, et al.. (2017). Pigs, Unlike Mice, Have Two Distinct Colonic Stem Cell Populations Similar to Humans That Respond to High-Calorie Diet prior to Insulin Resistance. Cancer Prevention Research. 10(8). 442–450. 10 indexed citations
12.
Radhakrishnan, Sridhar, Sung Woo Kim, Frank Shen, et al.. (2017). A food-based approach that targets interleukin-6, a key regulator of chronic intestinal inflammation and colon carcinogenesis. The Journal of Nutritional Biochemistry. 43. 11–17. 32 indexed citations
13.
Li, Qunhua & Feipeng Zhang. (2017). A Regression Framework for Assessing Covariate Effects on the Reproducibility of High-Throughput Experiments. Biometrics. 74(3). 803–813. 3 indexed citations
14.
Yang, Tao, Feipeng Zhang, Galip Gürkan Yardımcı, et al.. (2017). HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient. Genome Research. 27(11). 1939–1949. 283 indexed citations
15.
Zhang, Feipeng & Qunhua Li. (2017). A continuous threshold expectile model. Computational Statistics & Data Analysis. 116. 49–66. 20 indexed citations
16.
Zhang, Feipeng & Qunhua Li. (2017). Robust bent line regression. Journal of Statistical Planning and Inference. 185. 41–55. 19 indexed citations
17.
Li, Qunhua, Guobin He, & Ming Wen. (2016). Effects of changing cognitive factors on the quality of life in patients with functional dyspepsia. Zhonghua xiaohua zazhi. 36(11). 758–762. 1 indexed citations
18.
Lyu, Yafei & Qunhua Li. (2016). A semi-parametric statistical model for integrating gene expression profiles across different platforms. BMC Bioinformatics. 17(S1). 5–5. 15 indexed citations
19.
Kunz, Robert F., et al.. (2015). Multi-scale biological and physical modelling of the tumour micro-environment. Drug Discovery Today Disease Models. 16. 7–15. 2 indexed citations
20.
Li, Qunhua, Qiangwei Xia, Tiansong Wang, Marina Meilă, & Murray Hackett. (2006). Analysis of the stochastic variation in LTQ single scan mass spectra. Rapid Communications in Mass Spectrometry. 20(10). 1551–1557. 10 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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