Jun Yin

2.7k total citations
77 papers, 887 citations indexed

About

Jun Yin is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Jun Yin has authored 77 papers receiving a total of 887 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Oncology, 16 papers in Pulmonary and Respiratory Medicine and 16 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Jun Yin's work include Acute Lymphoblastic Leukemia research (12 papers), Cancer Genomics and Diagnostics (9 papers) and Statistical Methods in Clinical Trials (9 papers). Jun Yin is often cited by papers focused on Acute Lymphoblastic Leukemia research (12 papers), Cancer Genomics and Diagnostics (9 papers) and Statistical Methods in Clinical Trials (9 papers). Jun Yin collaborates with scholars based in United States, France and Italy. Jun Yin's co-authors include Dana B. Mukamel, Yue Li, Xueya Cai, Sumithra J. Mandrekar, Laurent G. Glance, Eli N. Perencevich, Ying Yuan, Marin L. Schweizer, Daniel J. Sargent and Richard M. Stone and has published in prestigious journals such as JAMA, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Jun Yin

71 papers receiving 867 citations

Peers

Jun Yin
Comparison fields: 5 of 98
  • Oncology 224
  • Molecular Biology 156
  • General Health Professions 143
  • Public Health, Environmental and Occupational Health 131
  • Pulmonary and Respiratory Medicine 119
Replace Matteo Franchi with:
Matteo Franchi Italy
Lee Cheng United States
Richard De Abreu Lourenço Australia
Zsuzsanna Jakab Hungary
David J. Hunter United States
Imran Rafi United Kingdom
Rajiv Mallick United States
Neerav Monga Canada
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Matteo Franchi Italy View profile →
Citations per field, relative to Jun Yin
Jun Yin · 1×
Citations per year, relative to Jun Yin
Jun Yin · 1×

Countries citing papers authored by Jun Yin

Since Specialization
Citations

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

Fields of papers citing papers by Jun Yin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun Yin

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

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 2
3 2
4 2
5 2
6 1
7 10
8 3
9 4
10 5
11 2
12 14
13 33
14 6
15 24
16 17
17 17
18 57
19 20
20 18

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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