Akito Natsume

871 total citations
9 papers, 684 citations indexed

About

Akito Natsume is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Genetics. According to data from OpenAlex, Akito Natsume has authored 9 papers receiving a total of 684 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 8 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Genetics. Recurrent topics in Akito Natsume's work include Monoclonal and Polyclonal Antibodies Research (8 papers), Glycosylation and Glycoproteins Research (7 papers) and Chronic Lymphocytic Leukemia Research (2 papers). Akito Natsume is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (8 papers), Glycosylation and Glycoproteins Research (7 papers) and Chronic Lymphocytic Leukemia Research (2 papers). Akito Natsume collaborates with scholars based in Japan and Singapore. Akito Natsume's co-authors include Rinpei Niwa, Mitsuo Satoh, Kenya Shitara, Masako Wakitani, Kazuhisa Uchida, Shigeru Iida, Tomoaki Nakagawa, Hiroyuki Takamura, Yukiko Shimizu and So Ohta and has published in prestigious journals such as Cancer Research, Biotechnology and Bioengineering and Journal of Immunological Methods.

In The Last Decade

Akito Natsume

9 papers receiving 653 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Akito Natsume Japan 9 543 442 294 142 78 9 684
Paul R. Hinton United States 8 449 0.8× 361 0.8× 205 0.7× 91 0.6× 28 0.4× 20 585
Naoko Yamane‐Ohnuki Japan 9 851 1.6× 964 2.2× 353 1.2× 134 0.9× 59 0.8× 9 1.1k
Björn Cochlovius Germany 12 341 0.6× 306 0.7× 262 0.9× 199 1.4× 21 0.3× 17 543
Ling C. Santora United States 7 397 0.7× 366 0.8× 182 0.6× 121 0.9× 23 0.3× 10 576
Kaitlyn Rogers United States 6 336 0.6× 161 0.4× 153 0.5× 138 1.0× 43 0.6× 11 482
Esohe Idusogie United States 6 446 0.8× 359 0.8× 275 0.9× 79 0.6× 147 1.9× 7 770
Bernd Hubner Germany 9 211 0.4× 276 0.6× 256 0.9× 73 0.5× 38 0.5× 15 579
Taichi Kuramochi United States 13 374 0.7× 285 0.6× 231 0.8× 88 0.6× 49 0.6× 23 605
Amy Haynes United States 4 355 0.7× 169 0.4× 155 0.5× 160 1.1× 45 0.6× 4 488
M. Josefina Coloma United States 6 339 0.6× 309 0.7× 168 0.6× 87 0.6× 17 0.2× 7 472

Countries citing papers authored by Akito Natsume

Since Specialization
Citations

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

Fields of papers citing papers by Akito Natsume

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Akito Natsume

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

All Works

9 of 9 papers shown
1.
Natsume, Akito, et al.. (2009). Engineered anti‐CD20 antibodies with enhanced complement‐activating capacity mediate potent anti‐lymphoma activity. Cancer Science. 100(12). 2411–2418. 34 indexed citations
2.
Nakagawa, Tomoaki, Akito Natsume, Mitsuo Satoh, & Rinpei Niwa. (2009). Nonfucosylated anti-CD20 antibody potentially induces apoptosis in lymphoma cells through enhanced interaction with FcγRIIIb on neutrophils. Leukemia Research. 34(5). 666–671. 13 indexed citations
3.
Natsume, Akito, Rinpei Niwa, & Mitsuo Satoh. (2009). Improving effector functions of antibodies for cancer treatment: Enhancing ADCC and CDC.. PubMed. 3. 7–16. 124 indexed citations
4.
Natsume, Akito, Hiroyuki Takamura, Tomoaki Nakagawa, et al.. (2008). Engineered Antibodies of IgG1/IgG3 Mixed Isotype with Enhanced Cytotoxic Activities. Cancer Research. 68(10). 3863–3872. 148 indexed citations
5.
Natsume, Akito. (2008). Improving effector functions of antibodies for cancer treatment: Enhancing ADCC and CDC. Drug Design Development and Therapy. 7–7. 87 indexed citations
7.
Natsume, Akito, Masako Wakitani, Naoko Yamane‐Ohnuki, et al.. (2005). Fucose removal from complex-type oligosaccharide enhances the antibody-dependent cellular cytotoxicity of single-gene-encoded antibody comprising a single-chain antibody linked the antibody constant region. Journal of Immunological Methods. 306(1-2). 93–103. 49 indexed citations
8.
Niwa, Rinpei, Akito Natsume, Masako Wakitani, et al.. (2005). IgG subclass-independent improvement of antibody-dependent cellular cytotoxicity by fucose removal from Asn297-linked oligosaccharides. Journal of Immunological Methods. 306(1-2). 151–160. 187 indexed citations
9.
Kawahara, Masahiro, Akito Natsume, Satoshi Terada, et al.. (2001). Replacing factor‐dependency with that for lysozyme: Affordable culture of IL‐6‐dependent hybridoma by transfecting artificial cell surface receptor. Biotechnology and Bioengineering. 74(5). 416–423. 13 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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