Akiko Tenma

464 total citations
10 papers, 320 citations indexed

About

Akiko Tenma is a scholar working on Molecular Biology, Immunology and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Akiko Tenma has authored 10 papers receiving a total of 320 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 4 papers in Immunology and 2 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Akiko Tenma's work include Immunotherapy and Immune Responses (3 papers), vaccines and immunoinformatics approaches (2 papers) and Cardiac Fibrosis and Remodeling (2 papers). Akiko Tenma is often cited by papers focused on Immunotherapy and Immune Responses (3 papers), vaccines and immunoinformatics approaches (2 papers) and Cardiac Fibrosis and Remodeling (2 papers). Akiko Tenma collaborates with scholars based in Japan, India and United States. Akiko Tenma's co-authors include Hironori Nakagami, Ryuichi Morishita, Munehisa Shimamura, H. Tomioka, Hitomi Kurinami, Hiroshi Koriyama, Zheng‐Da Pang, Hiroki Hayashi, Hiromi Rakugi and Jiao Sun and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and PLoS ONE.

In The Last Decade

Akiko Tenma

10 papers receiving 319 citations

Peers

Akiko Tenma

MB

IMMUN

PHYSI

ONCOL

NEURO

Lowella V. Fortuno United States

Ji Sun Moon South Korea

Vidyanand Anaparti Canada

Yanying Xu China

Xuqin Chen China

Peiman Shooshtarizadeh Canada

Jae-Ung Lee South Korea

Takashi Akasaki Japan

Dag Fadnes Norway

Nupur Aggarwal United States

Lowella V. Fortuno United States

Akiko Tenma

143 ×1.0

MB

76 ×0.7

IMMUN

32 ×0.5

PHYSI

65 ×1.1

ONCOL

13 ×0.3

NEURO

Citations per year, relative to Akiko Tenma Akiko Tenma (= 1×) peers Lowella V. Fortuno

Countries citing papers authored by Akiko Tenma

Since Specialization

Citations

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

Fields of papers citing papers by Akiko Tenma

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Akiko Tenma

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

All Works

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10 of 10 papers shown

1.

Yoshida, Shota, Hiroki Hayashi, Shunsuke Katsuki, et al.. (2024). A Vaccine Against Fibroblast Activation Protein Improves Murine Cardiac Fibrosis by Preventing the Accumulation of Myofibroblasts. Circulation Research. 136(1). 26–40. 5 indexed citations

2.

Hayashi, Hiroki, Jiao Sun, Shota Yoshida, et al.. (2023). Peptide-based vaccine targeting IL17A attenuates experimental spondyloarthritis in HLA-B27 transgenic rats. RMD Open. 9(1). e002851–e002851. 4 indexed citations

3.

Tenma, Akiko, et al.. (2021). Epitope Prediction of Antigen Protein Using Attention-based LSTM Network. Journal of Information Processing. 29(0). 321–327. 8 indexed citations

4.

Yoshida, Shota, Hironori Nakagami, Hiroki Hayashi, et al.. (2020). The CD153 vaccine is a senotherapeutic option for preventing the accumulation of senescent T cells in mice. Nature Communications. 11(1). 2482–2482. 106 indexed citations

5.

Nakamaru, Ryo, Hironori Nakagami, Hiroki Hayashi, et al.. (2020). A novel angiotensin II peptide vaccine without an adjuvant in mice. Journal of Hypertension. 39(1). 181–189. 4 indexed citations

6.

Tenma, Akiko, Hironori Nakagami, H. Tomioka, et al.. (2019). AJP001, a novel helper T‐cell epitope, induces a humoral immune response with activation of innate immunity when included in a peptide vaccine. FASEB BioAdvances. 1(12). 760–772. 4 indexed citations

7.

Tomioka, H., Hironori Nakagami, Akiko Tenma, et al.. (2014). Novel Anti-Microbial Peptide SR-0379 Accelerates Wound Healing via the PI3 Kinase/Akt/mTOR Pathway. PLoS ONE. 9(3). e92597–e92597. 46 indexed citations

8.

Shimamura, Munehisa, Yoshiaki Taniyama, Hironori Nakagami, et al.. (2014). Long-term expression of periostin during the chronic stage of ischemic stroke in mice. Hypertension Research. 37(6). 494–499. 16 indexed citations

9.

Nakagami, Hironori, Zheng‐Da Pang, Hitomi Kurinami, et al.. (2014). The dipeptidyl peptidase-4 inhibitor teneligliptin improved endothelial dysfunction and insulin resistance in the SHR/NDmcr-cp rat model of metabolic syndrome. Hypertension Research. 37(7). 629–635. 29 indexed citations

10.

Shimamura, Munehisa, Hironori Nakagami, Mariana Kiomy Osako, et al.. (2014). OPG/RANKL/RANK axis is a critical inflammatory signaling system in ischemic brain in mice. Proceedings of the National Academy of Sciences. 111(22). 8191–8196. 98 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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