Xiao‐Dan Ji

1.4k citations
20 papers · 1.1k · h-index 15

Impact in

    • Cancer, Hypoxia, and Metabolism
  • Cell Biology top 10%
    • Hippo pathway signaling and YAP/TAZ
    • Endoplasmic Reticulum Stress and Disease

Papers in

    • Viral Infectious Diseases and Gene Expression in Insects 3
    • Ubiquitin and proteasome pathways 2
    • RNA Research and Splicing 2
    • Protein purification and stability 2
    • Hippo pathway signaling and YAP/TAZ 4

Xiao‐Dan Ji

20 papers receiving 1.1k citations

Peers

Xiao‐Dan Ji
Comparison fields: 5 of 94
  • Cancer Research 183
  • Cell Biology 209
  • Molecular Biology 766
  • Oncology 205
  • Cellular and Molecular Neuroscience 101
Replace Francesca Grespi with:
Francesca Grespi Italy
Chae Young Hwang South Korea
Severine Gharbi Spain
Nachiket Vartak Germany
Mai Uesugi Japan
Zamal Ahmed United States
Takumi Kawabe Japan
С. И. Ткачев Russia
Xuejun Jiang China
Xiao‐Dan Ji relative to Francesca Grespi Italy Francesca Grespi's profile →
Citations per field
00.5×1.6×
Francesca Grespi · 1×
Citations per year

Countries citing papers authored by Xiao‐Dan Ji

Since Specialization
Citations

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

Fields of papers citing papers by Xiao‐Dan Ji

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiao‐Dan Ji. 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 Xiao‐Dan Ji. The network helps show where Xiao‐Dan Ji may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 2013173
2 2015113
3 2012104
4 201195
5 201190
6 201290
7 200885
8 201277
9 201464
10 201554
11 201440
12 200533
13 201631
14 202030
15 202321
16 200914
17 202112
18 20217
19 20224
20 20223

About Xiao‐Dan Ji

Xiao‐Dan Ji is a scholar working on Molecular Biology, Cell Biology, Cancer Research, Cellular and Molecular Neuroscience and Pharmacology, having authored 20 papers that have together received 1.1k indexed citations. Recurring topics across this work include Hippo pathway signaling and YAP/TAZ (4 papers), Viral Infectious Diseases and Gene Expression in Insects (3 papers), Cancer, Hypoxia, and Metabolism (3 papers), Ubiquitin and proteasome pathways (2 papers), Cancer, Lipids, and Metabolism (2 papers), Axon Guidance and Neuronal Signaling (2 papers), RNA Research and Splicing (2 papers) and Protein purification and stability (2 papers). The work is most often cited by research in Cancer Research (183 citations), Cell Biology (209 citations), Molecular Biology (766 citations), Oncology (205 citations) and Cellular and Molecular Neuroscience (101 citations). Xiao‐Dan Ji has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Kunxin Luo, Dong Xie, Daniel K. Nomura, Melinda M. Mulvihill, Jiang‐Sha Zhao, Shuo Shi, Yuezhen Deng, Sharon M. Louie, Daniel I. Benjamin and Huasong Lu. Their work appears in journals such as eLife, Biotechnology Progress, The Journal of Nutritional Biochemistry, Protein Expression and Purification and Gastroenterology.

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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