Ruowang Li

3.8k total citations · 2 hit papers
26 papers, 2.2k citations indexed

About

Ruowang Li is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Ruowang Li has authored 26 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 12 papers in Genetics and 7 papers in Cancer Research. Recurrent topics in Ruowang Li's work include Bioinformatics and Genomic Networks (10 papers), Genetic Associations and Epidemiology (8 papers) and Gene expression and cancer classification (7 papers). Ruowang Li is often cited by papers focused on Bioinformatics and Genomic Networks (10 papers), Genetic Associations and Epidemiology (8 papers) and Gene expression and cancer classification (7 papers). Ruowang Li collaborates with scholars based in United States, Israel and United Kingdom. Ruowang Li's co-authors include Marylyn D. Ritchie, Dokyoon Kim, Sarah A. Pendergrass, Emily Holzinger, Zhiping Weng, Oliver J. Rando, Lucas Fauquier, Hans A. Hofmann, Chengjian Li and Jeremy M. Shea and has published in prestigious journals such as Cell, Nature Communications and Nature Reviews Genetics.

In The Last Decade

Ruowang Li

25 papers receiving 2.2k citations

Hit Papers

Paternally Induced Transg... 2010 2026 2015 2020 2010 2015 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ruowang Li United States 13 1.5k 485 428 212 141 26 2.2k
Fabian Müller Germany 22 3.1k 2.0× 873 1.8× 510 1.2× 436 2.1× 182 1.3× 28 4.0k
Duygu Ucar United States 25 1.9k 1.2× 352 0.7× 126 0.3× 219 1.0× 234 1.7× 55 3.1k
Michael Rebhan Germany 12 2.9k 1.9× 756 1.6× 236 0.6× 351 1.7× 176 1.2× 21 3.8k
Y. Ann Chen United States 35 3.2k 2.1× 562 1.2× 262 0.6× 673 3.2× 210 1.5× 109 5.3k
Yongchao Ge United States 29 1.9k 1.2× 299 0.6× 102 0.2× 210 1.0× 136 1.0× 80 3.5k
Andrey A. Shabalin United States 24 1.7k 1.1× 942 1.9× 153 0.4× 332 1.6× 158 1.1× 61 2.7k
Pei Fen Kuan United States 30 1.9k 1.2× 378 0.8× 105 0.2× 453 2.1× 150 1.1× 91 2.9k
Huan Wu China 28 988 0.7× 455 0.9× 198 0.5× 245 1.2× 72 0.5× 118 2.4k
Elena Zotenko United States 17 1.7k 1.1× 318 0.7× 183 0.4× 276 1.3× 78 0.6× 27 2.1k

Countries citing papers authored by Ruowang Li

Since Specialization
Citations

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

Fields of papers citing papers by Ruowang Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ruowang Li

This figure shows the co-authorship network connecting the top 25 collaborators of Ruowang Li. A scholar is included among the top collaborators of Ruowang 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 Ruowang Li. Ruowang 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.
Li, Ruowang, Joseph D. Romano, Yong Chen, & Jason H. Moore. (2024). Centralized and Federated Models for the Analysis of Clinical Data. PubMed. 7(1). 179–199. 3 indexed citations
2.
Li, Ruowang, Rui Duan, Lifang He, & Jason H. Moore. (2023). Risk prediction: Methods, Challenges, and Opportunities. PubMed. 29. 650–653. 2 indexed citations
3.
Zhang, Elizabeth, Apurva S. Chitre, Oksana Polesskaya, et al.. (2023). Automated quantitative trait locus analysis (AutoQTL). BioData Mining. 16(1). 14–14. 4 indexed citations
4.
Tong, Jiayi, Rui Duan, Ruowang Li, et al.. (2023). Quantifying and correcting bias due to outcome dependent self-reported weights in longitudinal study of weight loss interventions. Scientific Reports. 13(1). 19078–19078.
5.
Li, Ruowang, Rui Duan, Xinyuan Zhang, et al.. (2021). Lossless integration of multiple electronic health records for identifying pleiotropy using summary statistics. Nature Communications. 12(1). 168–168. 5 indexed citations
6.
Li, Ruowang, Jiayi Tong, Rui Duan, Yong Chen, & Jason H. Moore. (2020). Evaluation of Phenotyping Errors on Polygenic Risk Score Predictions. 123–130. 1 indexed citations
7.
Li, Ruowang, Yong Chen, Marylyn D. Ritchie, & Jason H. Moore. (2020). Electronic health records and polygenic risk scores for predicting disease risk. Nature Reviews Genetics. 21(8). 493–502. 67 indexed citations
8.
Zhang, Xinyuan, Ruowang Li, & Marylyn D. Ritchie. (2020). Statistical Impact of Sample Size and Imbalance on Multivariate Analysis in silico and A Case Study in the UK Biobank.. PubMed. 2020. 1383–1391. 1 indexed citations
9.
Li, Ruowang, Rui Duan, Rachel L. Kember, et al.. (2019). A regression framework to uncover pleiotropy in large-scale electronic health record data. Journal of the American Medical Informatics Association. 26(10). 1083–1090. 6 indexed citations
10.
Li, Ruowang, Yong Chen, & Jason H. Moore. (2019). Integration of genetic and clinical information to improve imputation of data missing from electronic health records. Journal of the American Medical Informatics Association. 26(10). 1056–1063. 17 indexed citations
11.
Verma, Shefali S., Anastasia Lucas, Xinyuan Zhang, et al.. (2018). Collective feature selection to identify crucial epistatic variants. BioData Mining. 11(1). 5–5. 21 indexed citations
12.
Li, Ruowang, Dokyoon Kim, & Marylyn D. Ritchie. (2017). Methods to Analyze Big Data in Pharmacogenomics Research. Pharmacogenomics. 18(8). 807–820. 6 indexed citations
13.
Li, Ruowang, Scott Dudek, Dokyoon Kim, et al.. (2016). Identification of genetic interaction networks via an evolutionary algorithm evolved Bayesian network. BioData Mining. 9(1). 18–18. 6 indexed citations
14.
Kim, Dokyoon, Ruowang Li, Scott Dudek, & Marylyn D. Ritchie. (2015). Predicting censored survival data based on the interactions between meta-dimensional omics data in breast cancer. Journal of Biomedical Informatics. 56. 220–228. 24 indexed citations
15.
Ritchie, Marylyn D., Emily Holzinger, Ruowang Li, Sarah A. Pendergrass, & Dokyoon Kim. (2015). Methods of integrating data to uncover genotype–phenotype interactions. Nature Reviews Genetics. 16(2). 85–97. 672 indexed citations breakdown →
16.
Li, Ruowang, et al.. (2014). Knowledge-driven genomic interactions: an application in ovarian cancer. BioData Mining. 7(1). 20–20. 15 indexed citations
18.
Yıldırım, Özlem, Ruowang Li, Jui‐Hung Hung, et al.. (2011). Mbd3/NURD Complex Regulates Expression of 5-Hydroxymethylcytosine Marked Genes in Embryonic Stem Cells. Cell. 147(7). 1498–1510. 363 indexed citations
19.
Carone, Benjamin R., Lucas Fauquier, Naomi Habib, et al.. (2010). Paternally Induced Transgenerational Environmental Reprogramming of Metabolic Gene Expression in Mammals. Cell. 143(7). 1084–1096. 836 indexed citations breakdown →
20.
Dai, Quanqin, Yingnan Wang, Yu Zhang, et al.. (2009). Stability Study of PbSe Semiconductor Nanocrystals over Concentration, Size, Atmosphere, and Light Exposure. Langmuir. 25(20). 12320–12324. 65 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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