Tetsuhiro Harimoto

664 total citations · 1 hit paper
9 papers, 454 citations indexed

About

Tetsuhiro Harimoto is a scholar working on Biotechnology, Biomedical Engineering and Ecology. According to data from OpenAlex, Tetsuhiro Harimoto has authored 9 papers receiving a total of 454 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Biotechnology, 7 papers in Biomedical Engineering and 4 papers in Ecology. Recurrent topics in Tetsuhiro Harimoto's work include Cancer Research and Treatments (7 papers), 3D Printing in Biomedical Research (6 papers) and Bacteriophages and microbial interactions (4 papers). Tetsuhiro Harimoto is often cited by papers focused on Cancer Research and Treatments (7 papers), 3D Printing in Biomedical Research (6 papers) and Bacteriophages and microbial interactions (4 papers). Tetsuhiro Harimoto collaborates with scholars based in United States and Denmark. Tetsuhiro Harimoto's co-authors include Tal Danino, Kam W. Leong, Jaeseung Hahn, Courtney Coker, Jongwon Im, Kelly Pu, Nicholas Hou, Joanna Zhang, Fangda Li and Sreyan Chowdhury and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Biotechnology and Scientific Reports.

In The Last Decade

Tetsuhiro Harimoto

9 papers receiving 451 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A programmable encapsulation system improves delivery of therapeutic bacteria in mice

2022 171 citations Tetsuhiro Harimoto, Jaeseung Hahn et al. Nature Biotechnology profile →

Peers

Tetsuhiro Harimoto

BE

BIOTE

MB

ECOLO

GENET

Kelly Pu United States

Jongwon Im United States

Sreyan Chowdhury United States

Christopher Plescia United States

Jaeseung Hahn United States

Nhung Thi Hong Dinh South Korea

Xiang Luo United States

Rosa L. Vincent United States

Rosendo Lurı́a-Pérez Mexico

Candice R. Gurbatri United States

Kelly Pu United States

Tetsuhiro Harimoto

213 ×0.8

BE

242 ×1.0

BIOTE

132 ×0.8

MB

68 ×0.8

ECOLO

72 ×1.0

GENET

Citations per year, relative to Tetsuhiro Harimoto Tetsuhiro Harimoto (= 1×) peers Kelly Pu

Countries citing papers authored by Tetsuhiro Harimoto

Since Specialization

Citations

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

Fields of papers citing papers by Tetsuhiro Harimoto

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tetsuhiro Harimoto

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

All Works

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9 of 9 papers shown

1.

Harimoto, Tetsuhiro, Wei‐Hung Jung, & David Mooney. (2025). Delivering living medicines with biomaterials. Nature Reviews Materials. 10(3). 191–210. 16 indexed citations

2.

Hahn, Jaeseung, Suwan Ding, Jongwon Im, et al.. (2023). Bacterial therapies at the interface of synthetic biology and nanomedicine. Nature Reviews Bioengineering. 2(2). 120–135. 60 indexed citations

3.

Harimoto, Tetsuhiro, Jaeseung Hahn, Yuyu Chen, et al.. (2022). A programmable encapsulation system improves delivery of therapeutic bacteria in mice. Nature Biotechnology. 40(8). 1259–1269. 171 indexed citations breakdown →

4.

Deb, Dhruba, et al.. (2022). Design of combination therapy for engineered bacterial therapeutics in non-small cell lung cancer. Scientific Reports. 12(1). 21551–21551. 7 indexed citations

5.

Harimoto, Tetsuhiro, Dhruba Deb, & Tal Danino. (2022). A rapid screening platform to coculture bacteria within tumor spheroids. Nature Protocols. 17(10). 2216–2239. 21 indexed citations

6.

Chien, Tiffany, Tetsuhiro Harimoto, Courtney Coker, et al.. (2021). Enhancing the tropism of bacteria via genetically programmed biosensors. Nature Biomedical Engineering. 6(1). 94–104. 106 indexed citations

7.

Rossen, Ninna S., Priya N. Anandakumaran, Wenjie Luo, et al.. (2020). Injectable Therapeutic Organoids Using Sacrificial Hydrogels. iScience. 23(5). 101052–101052. 25 indexed citations

8.

Harimoto, Tetsuhiro, Zakary S. Singer, Joanna Zhang, et al.. (2019). Rapid screening of engineered microbial therapies in a 3D multicellular model. Proceedings of the National Academy of Sciences. 116(18). 9002–9007. 29 indexed citations

9.

Harimoto, Tetsuhiro & Tal Danino. (2019). Engineering bacteria for cancer therapy. Emerging Topics in Life Sciences. 3(5). 623–629. 19 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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