Shinya Rai

121 total papers · 1.7k total citations
45 papers, 379 citations indexed

About

Shinya Rai is a scholar working on Pathology and Forensic Medicine, Hematology and Genetics. According to data from OpenAlex, Shinya Rai has authored 45 papers receiving a total of 379 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Pathology and Forensic Medicine, 19 papers in Hematology and 18 papers in Genetics. Recurrent topics in Shinya Rai's work include Lymphoma Diagnosis and Treatment (20 papers), Chronic Lymphocytic Leukemia Research (15 papers) and Viral-associated cancers and disorders (8 papers). Shinya Rai is often cited by papers focused on Lymphoma Diagnosis and Treatment (20 papers), Chronic Lymphocytic Leukemia Research (15 papers) and Viral-associated cancers and disorders (8 papers). Shinya Rai collaborates with scholars based in Japan, United States and Philippines. Shinya Rai's co-authors include Itaru Matsumura, Hirokazu Tanaka, J. Luis Espinoza, Koji Izutsu, Yasuyoshi Morita, Hirohiko Shibayama, Yuzuru Kanakura, Hiro Tatetsu, Noriko Iwaki and Takayuki Ishikawa and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Shinya Rai

42 papers receiving 375 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Shinya Rai	161	149	126	102	70	45	379
Hong Liu	104 0.6×	100 0.7×	96 0.8×	144 1.4×	94 1.3×	33	431
Steve Abella	133 0.8×	114 0.8×	110 0.9×	62 0.6×	69 1.0×	21	388
Adrian Tempescul	132 0.8×	120 0.8×	124 1.0×	89 0.9×	109 1.6×	45	406
Hajime Yasuda	114 0.7×	73 0.5×	74 0.6×	92 0.9×	109 1.6×	54	361
J. Földi	114 0.7×	63 0.4×	106 0.8×	73 0.7×	80 1.1×	37	392
Nadia Khan	113 0.7×	201 1.3×	83 0.7×	53 0.5×	151 2.2×	37	430
Quoc‐Hung Le	129 0.8×	52 0.3×	154 1.2×	240 2.4×	73 1.0×	32	444
Parvaneh Vossough	148 0.9×	32 0.2×	160 1.3×	97 1.0×	76 1.1×	29	434
Shinsuke Mizutani	55 0.3×	126 0.8×	186 1.5×	121 1.2×	114 1.6×	50	395
Kazuki Taoka	127 0.8×	70 0.5×	206 1.6×	149 1.5×	84 1.2×	34	424

Countries citing papers authored by Shinya Rai

Since Specialization

Citations

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

Fields of papers citing papers by Shinya Rai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shinya Rai

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

All Works

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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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