Travis Y. Tu

726 total citations
8 papers, 449 citations indexed

About

Travis Y. Tu is a scholar working on Oncology, Immunology and Pathology and Forensic Medicine. According to data from OpenAlex, Travis Y. Tu has authored 8 papers receiving a total of 449 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Oncology, 6 papers in Immunology and 2 papers in Pathology and Forensic Medicine. Recurrent topics in Travis Y. Tu's work include Cancer Immunotherapy and Biomarkers (7 papers), Immune Cell Function and Interaction (4 papers) and Immunotherapy and Immune Responses (4 papers). Travis Y. Tu is often cited by papers focused on Cancer Immunotherapy and Biomarkers (7 papers), Immune Cell Function and Interaction (4 papers) and Immunotherapy and Immune Responses (4 papers). Travis Y. Tu collaborates with scholars based in United States. Travis Y. Tu's co-authors include Peter P. Lee, Christian Avalos, John H. Yim, Diana L. Simons, Chongkai Wang, Marwan Fakih, James Waisman, Xuyang Lu, Shawn T. Solomon and Ruo‐Qian Wang and has published in prestigious journals such as Journal of Clinical Investigation, Nature Communications and Nature Immunology.

In The Last Decade

Travis Y. Tu

8 papers receiving 448 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Travis Y. Tu United States	7	313	251	99	73	71	8	449
Changchang Lu China	9	260 0.8×	247 1.0×	131 1.3×	74 1.0×	58 0.8×	20	448
Zul Fazreen Singapore	6	282 0.9×	167 0.7×	72 0.7×	52 0.7×	122 1.7×	8	391
Jean‐Nicolas Lodewyckx Belgium	4	351 1.1×	277 1.1×	86 0.9×	56 0.8×	63 0.9×	7	455
Hanne Lind United States	5	336 1.1×	152 0.6×	150 1.5×	134 1.8×	128 1.8×	7	496
Anna M. Szpurka United States	10	265 0.8×	221 0.9×	114 1.2×	49 0.7×	107 1.5×	20	433
Sapna Yadavilli United States	7	364 1.2×	194 0.8×	141 1.4×	32 0.4×	52 0.7×	19	453
De Sen Wan China	9	247 0.8×	150 0.6×	119 1.2×	55 0.8×	85 1.2×	35	416
Yosuke Kubo Japan	7	222 0.7×	171 0.7×	82 0.8×	32 0.4×	48 0.7×	11	333
David Malaka United States	5	344 1.1×	159 0.6×	125 1.3×	228 3.1×	49 0.7×	6	537
Kezhuo Yu China	3	278 0.9×	306 1.2×	240 2.4×	108 1.5×	80 1.1×	3	547

Countries citing papers authored by Travis Y. Tu

Since Specialization

Citations

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

Fields of papers citing papers by Travis Y. Tu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Travis Y. Tu. 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 Travis Y. Tu. The network helps show where Travis Y. Tu may publish in the future.

Co-authorship network of co-authors of Travis Y. Tu

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

All Works

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8 of 8 papers shown

1.

He, Ting-Fang, Shawn T. Solomon, Travis Y. Tu, et al.. (2021). Spatial distribution of B cells and lymphocyte clusters as a predictor of triple-negative breast cancer outcome. npj Breast Cancer. 7(1). 84–84. 28 indexed citations

2.

He, Ting-Fang, Susan E. Yost, Paul Frankel, et al.. (2020). Multi-panel immunofluorescence analysis of tumor infiltrating lymphocytes in triple negative breast cancer: Evolution of tumor immune profiles and patient prognosis. PLoS ONE. 15(3). e0229955–e0229955. 20 indexed citations

3.

Wang, Lei, Diana L. Simons, Xuyang Lu, et al.. (2020). Breast cancer induces systemic immune changes on cytokine signaling in peripheral blood monocytes and lymphocytes. EBioMedicine. 52. 102631–102631. 60 indexed citations

4.

Wang, Lei, Diana L. Simons, Xuyang Lu, et al.. (2019). Connecting blood and intratumoral Treg cell activity in predicting future relapse in breast cancer. Nature Immunology. 20(9). 1220–1230. 125 indexed citations

5.

Fakih, Marwan, Ching Ouyang, Chongkai Wang, et al.. (2019). Immune overdrive signature in colorectal tumor subset predicts poor clinical outcome. Journal of Clinical Investigation. 129(10). 4464–4476. 62 indexed citations

6.

Egelston, Colt A., Christian Avalos, Travis Y. Tu, et al.. (2018). Human breast tumor-infiltrating CD8+ T cells retain polyfunctionality despite PD-1 expression. Nature Communications. 9(1). 4297–4297. 97 indexed citations

7.

Wang, Chongkai, Jun Gong, Travis Y. Tu, Peter P. Lee, & Marwan Fakih. (2018). Immune profiling of microsatellite instability-high and polymerase ε (POLE)-mutated metastatic colorectal tumors identifies predictors of response to anti-PD-1 therapy. Journal of Gastrointestinal Oncology. 9(3). 404–415. 55 indexed citations

8.

Egelston, Colt A., Christian Avalos, Yinghui Huang, et al.. (2018). Complex phenotyping of PD-1+ CD39+ exhausted CD8+ T cells in human carcinomas. The Journal of Immunology. 200(Supplement_1). 57.23–57.23. 2 indexed citations

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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