Hu Tan

503 citations
30 papers · 304 · h-index 8

Impact in

Papers in

    • Genomic variations and chromosomal abnormalities 5
    • Connective tissue disorders research 4
    • Genomics and Rare Diseases 4
    • RNA modifications and cancer 2

Hu Tan

28 papers receiving 302 citations

Peers

Hu Tan
Comparison fields: 5 of 51
  • Pediatrics, Perinatology and Child Health 184
  • Genetics 148
  • Infectious Diseases 51
  • Genetics 18
  • Cancer Research 25
Replace Siyuan Linpeng with:
Siyuan Linpeng China
Tamar Goldwaser United States
Elizabeth Scotchman United Kingdom
Fucheng Li China
Laura J. C. M. van Zutven Netherlands
George Rebello South Africa
Tingying Lei China
Erica Sanford Kobayashi United States
Chunyu Luo China
Jiansheng Xie China
Hu Tan relative to Siyuan Linpeng China Siyuan Linpeng's profile →
Citations per field
00.5×1.5×1.9×
Siyuan Linpeng · 1×
Citations per year

Countries citing papers authored by Hu Tan

Since Specialization
Citations

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

Fields of papers citing papers by Hu Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Hu Tan, 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 Hu Tan Line = papers co-authored together Hu Tan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019167
2 202014
3 201613
4 201712
5 201910
6 201810
7 20167
8 20187
9 20186
10 20186
11 20195
12 20155
13 20165
14 20195
15 20164
16 20154
17 20194
18 20203
19 20203
20 20203

About Hu Tan

Hu Tan is a scholar working on Genetics, Molecular Biology, Pediatrics, Perinatology and Child Health, Surgery and Nephrology, having authored 30 papers that have together received 304 indexed citations. Recurring topics across this work include Genomic variations and chromosomal abnormalities (5 papers), Connective tissue disorders research (4 papers), Prenatal Screening and Diagnostics (4 papers), Genomics and Rare Diseases (4 papers), Genetic factors in colorectal cancer (2 papers), Cancer Genomics and Diagnostics (2 papers), Fetal and Pediatric Neurological Disorders (2 papers) and RNA modifications and cancer (2 papers). The work is most often cited by research in Pediatrics, Perinatology and Child Health (184 citations), Genetics (148 citations), Infectious Diseases (51 citations), Genetics (18 citations) and Cancer Research (25 citations). Hu Tan has collaborated with scholars based in China, Malaysia and Australia. Frequent co-authors include Lingqian Wu, Siyuan Linpeng, Yingdi Liu, Yu Zhang, Mengnan Xu, David S. Cram, Feng Tian, Hongmin Zhu, Huaiyu Sun and Fuli Yu. Their work appears in journals such as Gene, Clinica Chimica Acta, Familial Cancer, European Journal of Medical Genetics and Genetics in Medicine.

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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