Jin-Fen Xiao

1.6k citations
16 papers · 759 indexed · 2 hit papers · h-index 9
Topics
Cancer Immunotherapy and Biomarkers (3 papers)interferon and immune responses (2 papers)CAR-T cell therapy research (2 papers)

In The Last Decade

Jin-Fen Xiao

13 papers receiving 753 citations

Hit Papers

Advances in bladder cancer biology and therapy202020262022202420202024100200300400

Peers

Jin-Fen Xiao
Comparison fields: 5 of 71
  • Molecular Biology 381
  • Surgery 312
  • Oncology 192
  • Pulmonary and Respiratory Medicine 187
  • Cancer Research 172
Replace Matthew D. Nitz with:
Matthew D. Nitz United States
Miwako Kakiuchi Japan
Masafumi Kumano Japan
Junxiang Wen China
Rongjun Guo United States
Kentaro Jingushi Japan
Chen Zhu China
Shereen Keleg Germany
Yanqiu Zhao China
Jin-Fen Xiao relative to Matthew D. Nitz United States Matthew D. Nitz's profile →
Citations per field
00.5×5.9×
Matthew D. Nitz · 1×
Citations per year

Countries citing papers authored by Jin-Fen Xiao

Since Specialization
Citations

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

Fields of papers citing papers by Jin-Fen Xiao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jin-Fen Xiao. 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 Jin-Fen Xiao. The network helps show where Jin-Fen Xiao may publish in the future.

Co-authorship network of co-authors of Jin-Fen Xiao

This figure shows the co-authorship network connecting the top 25 collaborators of Jin-Fen Xiao. A scholar is included among the top collaborators of Jin-Fen Xiao 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 Jin-Fen Xiao. Jin-Fen Xiao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
#WorkIndexed citations
1 0
2 0
3
Metabolic targeting of cancer associated fibroblasts overcomes T-cell exclusion and chemoresistance in soft-tissue sarcomasbreakdown →
52
4 12
5 48
6 32
7
Advances in bladder cancer biology and therapybreakdown →
456
8 20
9 8
10 1
11 1
12 30
13 0
14 71
15 1
16 27

About Jin-Fen Xiao

Jin-Fen Xiao is a scholar working on Health Informatics, Aging and Immunology, having authored 16 papers that have together received 759 indexed citations. Recurring topics across this work include Cancer Immunotherapy and Biomarkers (3 papers), interferon and immune responses (2 papers) and CAR-T cell therapy research (2 papers). The work is most often cited by research in Cancer Research (172 citations), Surgery (312 citations) and Oncology (192 citations). Jin-Fen Xiao has collaborated with scholars based in United States, Singapore and China. Frequent co-authors include Dan Theodorescu, Jason E. Duex, Linda L. Tran, Neeraj Agarwal, Andrew W. Caliri, Ling‐Wen Ding, Qiao‐Yang Sun, Yuko Nakayama, Wei Peng Yong and Lucia Torres Fernández. Their work appears in journals such as Nature Communications, Nature reviews. Cancer and Cancer Research.

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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