Ruofan Ding

576 total citations
20 papers, 340 citations indexed

About

Ruofan Ding is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Ruofan Ding has authored 20 papers receiving a total of 340 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 7 papers in Cancer Research and 2 papers in Genetics. Recurrent topics in Ruofan Ding's work include RNA modifications and cancer (10 papers), RNA Research and Splicing (8 papers) and Cancer-related molecular mechanisms research (6 papers). Ruofan Ding is often cited by papers focused on RNA modifications and cancer (10 papers), RNA Research and Splicing (8 papers) and Cancer-related molecular mechanisms research (6 papers). Ruofan Ding collaborates with scholars based in China, United States and Spain. Ruofan Ding's co-authors include Lili Xiong, Zhiyun Guo, Yalan Yang, Miranda Maki, Bao Zhang, Yiming Zhang, Ran Kang, Qingqing Huang, Wenrong Liu and Lei Li and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and PLoS ONE.

In The Last Decade

Ruofan Ding

18 papers receiving 338 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ruofan Ding China 8 273 184 32 21 14 20 340
Gabrijela Dumbović United States 9 247 0.9× 142 0.8× 42 1.3× 15 0.7× 13 0.9× 17 308
María Tiana Spain 9 212 0.8× 140 0.8× 27 0.8× 19 0.9× 11 0.8× 13 267
Ângela Aguirres Fachel Brazil 9 287 1.1× 219 1.2× 28 0.9× 17 0.8× 10 0.7× 11 382
Yuzhong Jeff Meng United States 2 210 0.8× 144 0.8× 33 1.0× 30 1.4× 9 0.6× 2 284
Courtney K. JnBaptiste United States 5 521 1.9× 313 1.7× 22 0.7× 29 1.4× 10 0.7× 5 573
Xintao Wei United States 6 438 1.6× 114 0.6× 29 0.9× 32 1.5× 5 0.4× 7 500
Mahdieh Jadaliha United States 6 461 1.7× 285 1.5× 16 0.5× 13 0.6× 10 0.7× 8 506
Haiqing Xiong China 7 397 1.5× 81 0.4× 29 0.9× 30 1.4× 12 0.9× 12 418
Ana Petracovici United States 4 229 0.8× 137 0.7× 16 0.5× 30 1.4× 6 0.4× 4 264
Tiffany R. Baker United States 4 228 0.8× 91 0.5× 30 0.9× 11 0.5× 9 0.6× 6 285

Countries citing papers authored by Ruofan Ding

Since Specialization
Citations

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

Fields of papers citing papers by Ruofan Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ruofan Ding

This figure shows the co-authorship network connecting the top 25 collaborators of Ruofan Ding. A scholar is included among the top collaborators of Ruofan Ding 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 Ruofan Ding. Ruofan Ding 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.
Ding, Ruofan, Wenyan Chen, Hao Rong, et al.. (2024). eRNA-IDO: A One-stop Platform for Identification, Interactome Discovery, and Functional Annotation of Enhancer RNAs. Genomics Proteomics & Bioinformatics. 22(4). 4 indexed citations
2.
Ding, Ruofan, Qiang Chen, Fulai Li, et al.. (2024). Nphos: Database and Predictor of Protein N -phosphorylation. Genomics Proteomics & Bioinformatics. 22(3). 2 indexed citations
3.
Chen, Wenyan, Xuelian Ma, Ruofan Ding, et al.. (2024). A distinct class of pan-cancer susceptibility genes revealed by an alternative polyadenylation transcriptome-wide association study. Nature Communications. 15(1). 1729–1729. 6 indexed citations
4.
Ding, Ruofan, et al.. (2024). Mining Real-World Big Data to Characterize Adverse Drug Reaction Quantitatively: Mixed Methods Study. Journal of Medical Internet Research. 26. e48572–e48572. 4 indexed citations
5.
Ding, Ruofan, Xuelian Ma, Shouhong Guang, et al.. (2023). xQTLbiolinks: a comprehensive and scalable tool for integrative analysis of molecular QTLs. Briefings in Bioinformatics. 25(1). 9 indexed citations
6.
Li, Lei, Xuelian Ma, Ya Cui, et al.. (2023). Immune-response 3′UTR alternative polyadenylation quantitative trait loci contribute to variation in human complex traits and diseases. Nature Communications. 14(1). 8347–8347. 7 indexed citations
7.
Ding, Ruofan, et al.. (2023). scQTLbase: an integrated human single-cell eQTL database. Nucleic Acids Research. 52(D1). D1010–D1017. 14 indexed citations
8.
Ding, Ruofan, Yun Zhang, Pan You, et al.. (2022). Discovering Innate Driver Variants for Risk Assessment of Early Colorectal Cancer Metastasis. Frontiers in Oncology. 12. 898117–898117.
9.
Ding, Ruofan, Wenyan Chen, Gao Wang, et al.. (2022). Using population-scale transcriptomic and genomic data to map 3′ UTR alternative polyadenylation quantitative trait loci. STAR Protocols. 3(3). 101566–101566. 2 indexed citations
10.
Ding, Ruofan, et al.. (2022). Determination of the Amino Acid Recruitment Order in Early Life by Genome-Wide Analysis of Amino Acid Usage Bias. Biomolecules. 12(2). 171–171. 5 indexed citations
11.
Ma, Xuelian, Ruofan Ding, Shouhong Guang, et al.. (2022). ipaQTL-atlas: an atlas of intronic polyadenylation quantitative trait loci across human tissues. Nucleic Acids Research. 51(D1). D1046–D1052. 9 indexed citations
12.
Ding, Ruofan, Qian Yu, Ke Liu, et al.. (2021). Gene network analyses unveil possible molecular basis underlying drug-induced glaucoma. BMC Medical Genomics. 14(1). 109–109. 2 indexed citations
13.
Liu, Wenrong, Yin Zhang, Shuquan Rao, et al.. (2019). Down-regulation expression of TGFB2-AS1 inhibits the proliferation, migration, invasion and induces apoptosis in HepG2 cells. Genes & Genomics. 41(8). 951–959. 7 indexed citations
14.
Xiong, Lili, Ran Kang, Ruofan Ding, et al.. (2018). Genome-wide Identification and Characterization of Enhancers Across 10 Human Tissues. International Journal of Biological Sciences. 14(10). 1321–1332. 25 indexed citations
15.
Kang, Ran, Yiming Zhang, Qingqing Huang, et al.. (2018). EnhancerDB: a resource of transcriptional regulation in the context of enhancers. Database. 2019. 28 indexed citations
16.
Liu, Wenrong, Ruofan Ding, Yiming Zhang, et al.. (2017). Transcriptome profiling analysis of differentially expressed mRNAs and lncRNAs in HepG2 cells treated with peptide 9R-P201. Biotechnology Letters. 39(11). 1639–1647. 6 indexed citations
17.
Zhang, Yiming, Ran Kang, Wenrong Liu, et al.. (2017). Identification and Analysis of P53-Mediated Competing Endogenous RNA Network in Human Hepatocellular Carcinoma. International Journal of Biological Sciences. 13(9). 1213–1221. 17 indexed citations
18.
Yang, Yalan, Wenrong Liu, Ruofan Ding, et al.. (2016). Comprehensive Expression Profiling and Functional Network Analysis of p53-Regulated MicroRNAs in HepG2 Cells Treated with Doxorubicin. PLoS ONE. 11(2). e0149227–e0149227. 16 indexed citations
19.
Guo, Zhiyun, Miranda Maki, Ruofan Ding, et al.. (2014). Genome-wide survey of tissue-specific microRNA and transcription factor regulatory networks in 12 tissues. Scientific Reports. 4(1). 5150–5150. 176 indexed citations
20.

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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