Hiroshi Hinou

2.9k total citations
108 papers, 2.4k citations indexed

About

Hiroshi Hinou is a scholar working on Molecular Biology, Organic Chemistry and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Hiroshi Hinou has authored 108 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 93 papers in Molecular Biology, 68 papers in Organic Chemistry and 21 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Hiroshi Hinou's work include Glycosylation and Glycoproteins Research (80 papers), Carbohydrate Chemistry and Synthesis (64 papers) and Monoclonal and Polyclonal Antibodies Research (21 papers). Hiroshi Hinou is often cited by papers focused on Glycosylation and Glycoproteins Research (80 papers), Carbohydrate Chemistry and Synthesis (64 papers) and Monoclonal and Polyclonal Antibodies Research (21 papers). Hiroshi Hinou collaborates with scholars based in Japan, Spain and United States. Hiroshi Hinou's co-authors include Shin‐Ichiro Nishimura, Takahiko Matsushita, H. Shimizu, Masaki Kurogochi, Hirosato Kondo, Masataka Fumoto, Fayna García‐Martin, Naoki Fujitani, Maho Amano and Tetsu Ohashi and has published in prestigious journals such as Journal of the American Chemical Society, Angewandte Chemie International Edition and PLoS ONE.

In The Last Decade

Hiroshi Hinou

104 papers receiving 2.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hiroshi Hinou Japan 31 2.0k 1.2k 413 282 252 108 2.4k
Jennifer J. Kohler United States 28 2.3k 1.2× 1.1k 0.9× 395 1.0× 430 1.5× 184 0.7× 78 2.8k
Marian C. Bryan United States 21 2.1k 1.1× 1.8k 1.4× 463 1.1× 414 1.5× 134 0.5× 40 3.1k
Masaki Kurogochi Japan 27 1.6k 0.8× 813 0.7× 324 0.8× 251 0.9× 325 1.3× 51 1.8k
Olivier Renaudet France 31 2.4k 1.2× 1.6k 1.3× 528 1.3× 315 1.1× 152 0.6× 106 3.0k
John A. W. Kruijtzer Netherlands 31 1.9k 1.0× 886 0.7× 409 1.0× 223 0.8× 194 0.8× 76 3.0k
Shixian Lin China 25 1.9k 1.0× 1.0k 0.8× 294 0.7× 154 0.5× 197 0.8× 52 2.5k
Martin D. Witte Netherlands 27 1.7k 0.9× 1.2k 1.0× 350 0.8× 204 0.7× 63 0.3× 83 2.7k
Danielle H. Dube United States 18 2.4k 1.2× 1.6k 1.3× 659 1.6× 444 1.6× 195 0.8× 33 3.0k
Huchen Zhou China 27 1.7k 0.9× 980 0.8× 213 0.5× 117 0.4× 149 0.6× 54 2.9k
Valentin Wittmann Germany 32 2.4k 1.2× 1.9k 1.6× 544 1.3× 251 0.9× 84 0.3× 102 3.1k

Countries citing papers authored by Hiroshi Hinou

Since Specialization
Citations

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

Fields of papers citing papers by Hiroshi Hinou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hiroshi Hinou

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

All Works

20 of 20 papers shown
1.
Hinou, Hiroshi, et al.. (2024). Integration of MALDI glycotyping and NMR analysis to uncover an O-antigen substructure from pathogenic Escherichia coli O111. International Journal of Biological Macromolecules. 282(Pt 5). 137178–137178. 1 indexed citations
2.
Hinou, Hiroshi, et al.. (2024). MALDI glycotyping of O-antigens from a single colony of gram-negative bacteria. Scientific Reports. 14(1). 12719–12719. 6 indexed citations
3.
Hinou, Hiroshi, et al.. (2023). Sodium-Doped 3-Amino-4-hydroxybenzoic Acid: Rediscovered Matrix for Direct MALDI Glycotyping of O-Linked Glycopeptides and Intact Mucins. International Journal of Molecular Sciences. 24(23). 16836–16836. 2 indexed citations
4.
Ludwig, Anna‐Kristin, Seiya Kikuchi, Rika Ochi, et al.. (2023). Altering the Modular Architecture of Galectins Affects its Binding with Synthetic α‐Dystroglycan O‐Mannosylated Core M1 Glycoconjugates In situ. ChemBioChem. 24(14). e202200783–e202200783.
5.
Hinou, Hiroshi. (2023). DHB Matrix with Additives for Direct MALDI Mass Spectrometry of Carbohydrates and Glycoconjugates. Trends in Glycoscience and Glycotechnology. 35(204). J19–J22.
6.
7.
Ludwig, Anna‐Kristin, Hiroyuki Kumeta, Seiya Kikuchi, et al.. (2022). Exploring the In situ pairing of human galectins toward synthetic O-mannosylated core M1 glycopeptides of α-dystroglycan. Scientific Reports. 12(1). 17800–17800. 2 indexed citations
8.
Navo, Claudio D., J. Castro-López, Ana Guerreiro, et al.. (2020). Synthesis, conformational analysis and in vivo assays of an anti-cancer vaccine that features an unnatural antigen based on an sp2-iminosugar fragment. Chemical Science. 11(15). 3996–4006. 29 indexed citations
9.
10.
Hideshima, Sho, Hiroki Hayashi, Hiroshi Hinou, et al.. (2019). Glycan-immobilized dual-channel field effect transistor biosensor for the rapid identification of pandemic influenza viral particles. Scientific Reports. 9(1). 11616–11616. 31 indexed citations
11.
12.
Matsushita, Takahiko, et al.. (2013). A straightforward protocol for the preparation of high performance microarray displaying synthetic MUC1 glycopeptides. Biochimica et Biophysica Acta (BBA) - General Subjects. 1840(3). 1105–1116. 31 indexed citations
13.
Hinou, Hiroshi, Masaki Kurogochi, Xiao‐Dong Gao, et al.. (2011). A Strategy for Neuraminidase Inhibitors Using Mechanism‐Based Labeling Information. Chemistry - An Asian Journal. 6(4). 1048–1056. 7 indexed citations
14.
Hashimoto, Ryo, Naoki Fujitani, Yasuhiro Takegawa, et al.. (2011). An Efficient Approach for the Characterization of Mucin‐Type Glycopeptides: The Effect of O‐Glycosylation on the Conformation of Synthetic Mucin Peptides. Chemistry - A European Journal. 17(8). 2393–2404. 30 indexed citations
15.
García‐Martin, Fayna, et al.. (2011). An efficient protocol for the solid-phase synthesis of glycopeptides under microwave irradiation. Organic & Biomolecular Chemistry. 10(8). 1612–1612. 20 indexed citations
16.
Sakagami, Masahiro, Hiroto Yamaguchi, Hiroko Togame, et al.. (2010). Potent inhibitor scaffold against Trypanosoma cruzi trans-sialidase. Bioorganic & Medicinal Chemistry. 18(4). 1633–1640. 44 indexed citations
17.
18.
Fumoto, Masataka, Hiroshi Hinou, Takahiko Matsushita, et al.. (2005). Molecular Transporter Between Polymer Platforms: Highly Efficient Chemoenzymatic Glycopeptide Synthesis by the Combined Use of Solid‐Phase and Water‐Soluble Polymer Supports. Angewandte Chemie International Edition. 44(17). 2534–2537. 35 indexed citations
19.
Hinou, Hiroshi. (2000). . Trends in Glycoscience and Glycotechnology. 12(65). 185–190. 1 indexed citations
20.
Hinou, Hiroshi, Hidehiro Kurosawa, Koji Matsuoka, Daiyo Terunuma, & Hiroyoshi Kuzuhara. (1999). Novel synthesis of l-iduronic acid using trehalose as the disaccharidic starting material. Tetrahedron Letters. 40(8). 1501–1504. 31 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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