Tao Long

1.2k citations
27 papers · 865 · h-index 19

Impact in

Papers in

    • RNA and protein synthesis mechanisms 7
    • RNA modifications and cancer 6
    • Cancer-related gene regulation 5
    • Wnt/β-catenin signaling in development and cancer 2
    • Cholesterol and Lipid Metabolism 5

Tao Long

26 papers receiving 853 citations

Peers

Tao Long
Comparison fields: 5 of 108
  • Structural Biology 15
  • Health Informatics 13
  • Cancer Research 125
  • Molecular Biology 542
  • Biochemistry 50
Replace Fanghua Li with:
Fanghua Li China
James Lawrence United States
Kristin Roman United States
Yinan Xiao China
Ningning Zhang China
Rodney L. Sparks United States
Mai Sun United States
Salisha Hill United States
Zhihui Song China
Mizuho Nakayama Japan
Tao Long relative to Fanghua Li China Fanghua Li's profile →
Citations per field
00.5×3.3×
Fanghua Li · 1×
Citations per year

Countries citing papers authored by Tao Long

Since Specialization
Citations

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

Fields of papers citing papers by Tao Long

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201787
2 202076
3 202274
4 202158
5 202057
6 202056
7 201648
8 202046
9 201944
10 200841
11 201533
12 201833
13 201725
14 202323
15 202122
16 202122
17 198021
18 201519
19 201919
20 202016

About Tao Long

Tao Long is a scholar working on Molecular Biology, Surgery, Cell Biology, Endocrinology, Diabetes and Metabolism and Oncology, having authored 27 papers that have together received 865 indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (7 papers), RNA modifications and cancer (6 papers), Cholesterol and Lipid Metabolism (5 papers), Cancer-related gene regulation (5 papers), Wnt/β-catenin signaling in development and cancer (2 papers), Endoplasmic Reticulum Stress and Disease (2 papers), Pharmacogenetics and Drug Metabolism (2 papers) and Lipid metabolism and biosynthesis (2 papers). The work is most often cited by research in Structural Biology (15 citations), Health Informatics (13 citations), Cancer Research (125 citations), Molecular Biology (542 citations) and Biochemistry (50 citations). Tao Long has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Xiaochun Li, Xiaofeng Qi, Abdirahman Hassan, Yingyuan Sun, En‐Duo Wang, Ru‐Juan Liu, Jing Li, Nadia Elghobashi‐Meinhardt, Hao Li and Xiao‐Song Xie. Their work appears in journals such as Nucleic Acids Research, Nature Communications, Nature, Cell and Nature Structural & Molecular Biology.

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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