Joe Yeong

84 total papers · 1.8k total citations
28 papers, 530 citations indexed

About

Joe Yeong is a scholar working on Molecular Biology, Oncology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Joe Yeong has authored 28 papers receiving a total of 530 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 10 papers in Oncology and 6 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Joe Yeong's work include Single-cell and spatial transcriptomics (7 papers), Cancer Immunotherapy and Biomarkers (4 papers) and COVID-19 Clinical Research Studies (3 papers). Joe Yeong is often cited by papers focused on Single-cell and spatial transcriptomics (7 papers), Cancer Immunotherapy and Biomarkers (4 papers) and COVID-19 Clinical Research Studies (3 papers). Joe Yeong collaborates with scholars based in Singapore, Australia and China. Joe Yeong's co-authors include Jeffrey Chun Tatt Lim, Mai Chan Lau, Xingjie Shi, Yi Yang, Jin Liu, Wei Liu, Jabed Iqbal, Aye Aye Thike, Puay Hoon Tan and Denise Goh and has published in prestigious journals such as Nucleic Acids Research, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Joe Yeong

26 papers receiving 523 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Joe Yeong 220 203 119 106 98 28 530
Mihaela Ignat 260 1.2× 96 0.5× 196 1.6× 143 1.3× 53 0.5× 22 613
Yasunori Yoshimoto 209 0.9× 199 1.0× 118 1.0× 65 0.6× 47 0.5× 39 547
J. H. Doroshow 186 0.8× 247 1.2× 68 0.6× 99 0.9× 48 0.5× 30 542
Timothy T. C. Yip 229 1.0× 249 1.2× 72 0.6× 48 0.5× 96 1.0× 18 561
Carla M. van Herpen 195 0.9× 321 1.6× 98 0.8× 110 1.0× 52 0.5× 27 603
Ting‐Chun Kuo 148 0.7× 265 1.3× 246 2.1× 71 0.7× 52 0.5× 46 608
Jing Li 144 0.7× 188 0.9× 187 1.6× 38 0.4× 77 0.8× 30 609
Mattia Riefolo 224 1.0× 238 1.2× 45 0.4× 34 0.3× 115 1.2× 33 523
Judith Diment 91 0.4× 111 0.5× 100 0.8× 183 1.7× 72 0.7× 28 575
Yuqian Huang 118 0.5× 174 0.9× 79 0.7× 90 0.8× 61 0.6× 33 481

Countries citing papers authored by Joe Yeong

Since Specialization
Citations

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

Fields of papers citing papers by Joe Yeong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joe Yeong

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

All Works

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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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