Yuting Guan

2.5k citations
44 papers · 1.0k · h-index 17

Impact in

Papers in

    • CRISPR and Genetic Engineering 10
    • Renal and related cancers 6
    • Epigenetics and DNA Methylation 6
    • Pluripotent Stem Cells Research 4
    • RNA regulation and disease 3
    • Virus-based gene therapy research 3

Yuting Guan

39 papers receiving 997 citations

Peers

Yuting Guan
Comparison fields: 5 of 101
  • Business and International Management 41
  • Aging 35
  • Nephrology 95
  • Molecular Biology 663
  • Genetics 264
Replace Majid Mojarrad with:
Majid Mojarrad Iran
Rina Hashimoto Japan
Emmanouil Athanasakis Italy
Yongjie Chen China
Zhiling Li China
Loïc Rolas United Kingdom
Seokho Kim South Korea
Serena Tedesco Italy
Kohei Miyata Japan
Yuting Guan relative to Majid Mojarrad Iran Majid Mojarrad's profile →
Citations per field
00.5×10×15.8×
Majid Mojarrad · 1×
Citations per year

Countries citing papers authored by Yuting Guan

Since Specialization
Citations

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

Fields of papers citing papers by Yuting Guan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Yuting Guan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Yuting Guan Line = papers co-authored together Yuting Guan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014155
2 2016133
3 201577
4 201959
5 201959
6 202155
7 202150
8 201343
9 201343
10 201541
11 201932
12 201432
13 202226
14 202020
15 202419
16 202019
17 202316
18 202311
19 202411
20 201411

About Yuting Guan

Yuting Guan is a scholar working on Molecular Biology, Genetics, Surgery, Nephrology and Cellular and Molecular Neuroscience, having authored 44 papers that have together received 1.0k indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (10 papers), Renal and related cancers (6 papers), Epigenetics and DNA Methylation (6 papers), Pluripotent Stem Cells Research (4 papers), Chronic Kidney Disease and Diabetes (3 papers), Catalytic Processes in Materials Science (3 papers), RNA regulation and disease (3 papers) and Virus-based gene therapy research (3 papers). The work is most often cited by research in Business and International Management (41 citations), Aging (35 citations), Nephrology (95 citations), Molecular Biology (663 citations) and Genetics (264 citations). Yuting Guan has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Dali Li, Mingyao Liu, Liren Wang, Yanjiao Shao, Lijuan Wu, Katalin Suszták, Xueyun Ma, Yuting Chen, Meizhen Liu and Liang Li. Their work appears in journals such as Journal of the American Society of Nephrology, Nature Communications, Advanced Science, Molecular Therapy and Molecular Cell.

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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