Timothy Chu

2.3k citations
25 papers · 847 · h-index 12

Impact in

  • Aging top 5%
    • Genetics, Aging, and Longevity in Model Organisms
  • Immunology top 10%
    • Immune Cell Function and Interaction
    • T-cell and B-cell Immunology
    • Immune cells in cancer
    • Immunotherapy and Immune Responses

Papers in

    • Immune Cell Function and Interaction 7
    • T-cell and B-cell Immunology 5
    • IL-33, ST2, and ILC Pathways 3
    • Immune cells in cancer 3

Timothy Chu

25 papers receiving 834 citations

Peers

Timothy Chu
Comparison fields: 5 of 111
  • Aging 72
  • Immunology 288
  • Physiology 201
  • Biological Psychiatry 17
  • Oncology 165
Replace Xiaoyong Ge with:
Xiaoyong Ge China
Denis A. Mogilenko Russia
Mengyuan Kan China
Ronald Allan M. Panganiban United States
Kashyap Patel United Kingdom
Juli Bai United States
Giovanni Santacroce Italy
Paul J. Gallins United States
Shigeru Negoro Japan
Sverre Holm Norway
Timothy Chu relative to Xiaoyong Ge China Xiaoyong Ge's profile →
Citations per field
00.5×7.7×
Xiaoyong Ge · 1×
Citations per year

Countries citing papers authored by Timothy Chu

Since Specialization
Citations

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

Fields of papers citing papers by Timothy Chu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009201
2 2012115
3 2018107
4 202098
5 202070
6 201738
7 201634
8 202134
9 202332
10 201528
11 202214
12 202212
13 202111
14 201711
15 201811
16 201610
17 20224
18 20234
19 20204
20 20182

About Timothy Chu

Timothy Chu is a scholar working on Immunology, Molecular Biology, Artificial Intelligence, Oncology and Computational Theory and Mathematics, having authored 25 papers that have together received 847 indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (7 papers), T-cell and B-cell Immunology (5 papers), IL-33, ST2, and ILC Pathways (3 papers), Immune cells in cancer (3 papers), Machine Learning and Algorithms (2 papers), Stochastic Gradient Optimization Techniques (2 papers), Adipose Tissue and Metabolism (2 papers) and Cancer Immunotherapy and Biomarkers (2 papers). The work is most often cited by research in Aging (72 citations), Immunology (288 citations), Physiology (201 citations), Biological Psychiatry (17 citations) and Oncology (165 citations). Timothy Chu has collaborated with scholars based in United States, Japan and Hong Kong. Frequent co-authors include Brian S. Sheridan, Camille Khairallah, James R. Mitchell, Zhijuan Qiu, Wei Peng, Cristina Müller, Lauren Robertson, Natascha Goemaere, Wilfred F. J. van IJcken and Pedro Mejia. Their work appears in journals such as Mucosal Immunology, Cancer Discovery, Frontiers in Immunology, npj Genomic Medicine and The Journal of Experimental Medicine.

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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