Mako Takami

1.1k total citations
9 papers, 850 citations indexed

About

Mako Takami is a scholar working on Physiology, Oncology and Pharmacology. According to data from OpenAlex, Mako Takami has authored 9 papers receiving a total of 850 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Physiology, 4 papers in Oncology and 3 papers in Pharmacology. Recurrent topics in Mako Takami's work include Alzheimer's disease research and treatments (9 papers), Drug Transport and Resistance Mechanisms (4 papers) and Cholinesterase and Neurodegenerative Diseases (3 papers). Mako Takami is often cited by papers focused on Alzheimer's disease research and treatments (9 papers), Drug Transport and Resistance Mechanisms (4 papers) and Cholinesterase and Neurodegenerative Diseases (3 papers). Mako Takami collaborates with scholars based in Japan. Mako Takami's co-authors include Yasuo Ihara, Satoru Funamoto, Maho Morishima‐Kawashima, Yu Nagashima, Y Sano, Seiko Ishihara, Masayasu Okochi, Shinji Tagami, Nobuto Kakuda and Naoshi Dohmae and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Neuroscience and Cell Reports.

In The Last Decade

Mako Takami

9 papers receiving 831 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mako Takami Japan	8	753	456	277	227	109	9	850
Sam Lismont Belgium	9	740 1.0×	481 1.1×	222 0.8×	189 0.8×	152 1.4×	12	917
Alexandra Tolia Belgium	11	783 1.0×	641 1.4×	294 1.1×	192 0.8×	240 2.2×	12	1.1k
Hanna Laudon Sweden	14	777 1.0×	425 0.9×	279 1.0×	158 0.7×	148 1.4×	18	1000
Hue T. Kha United States	5	751 1.0×	442 1.0×	347 1.3×	289 1.3×	109 1.0×	6	998
Charlotte Stenh Sweden	4	958 1.3×	629 1.4×	222 0.8×	207 0.9×	141 1.3×	4	1.1k
Thomas B. Ladd United States	18	715 0.9×	517 1.1×	228 0.8×	186 0.8×	164 1.5×	31	1.2k
Manasi Benurwar United Kingdom	9	505 0.7×	347 0.8×	170 0.6×	119 0.5×	107 1.0×	9	753
Yu Tanimura Japan	6	474 0.6×	285 0.6×	162 0.6×	136 0.6×	66 0.6×	7	548
Diana Dominguez Switzerland	11	519 0.7×	409 0.9×	230 0.8×	156 0.7×	121 1.1×	12	829
Paul E. Fraser Canada	10	786 1.0×	585 1.3×	166 0.6×	115 0.5×	106 1.0×	12	957

Countries citing papers authored by Mako Takami

Since Specialization

Citations

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

Fields of papers citing papers by Mako Takami

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mako Takami

This figure shows the co-authorship network connecting the top 25 collaborators of Mako Takami. A scholar is included among the top collaborators of Mako Takami 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 Mako Takami. Mako Takami 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

Kakuda, Nobuto, Mako Takami, Masayasu Okochi, et al.. (2021). Switched Aβ43 generation in familial Alzheimer’s disease with presenilin 1 mutation. Translational Psychiatry. 11(1). 558–558. 7 indexed citations

Tagami, Shinji, Kanta Yanagida, Takashi Kodama, et al.. (2017). Semagacestat Is a Pseudo-Inhibitor of γ-Secretase. Cell Reports. 21(1). 259–273. 55 indexed citations

Yanagida, Kanta, Takashi Kodama, Takeshi Tomonaga, et al.. (2017). Identification of Small Peptides in Human Cerebrospinal Fluid upon Amyloid-β Degradation. Neurodegenerative Diseases. 17(2-3). 103–109. 1 indexed citations

Matsumura, Nobutaka, Mako Takami, Masayasu Okochi, et al.. (2013). γ-Secretase Associated with Lipid Rafts. Journal of Biological Chemistry. 289(8). 5109–5121. 81 indexed citations

Okochi, Masayasu, Shinji Tagami, Kanta Yanagida, et al.. (2013). γ-Secretase Modulators and Presenilin 1 Mutants Act Differently on Presenilin/γ-Secretase Function to Cleave Aβ42 and Aβ43. Cell Reports. 3(1). 42–51. 100 indexed citations

Takami, Mako & Satoru Funamoto. (2012). γ-Secretase-Dependent Proteolysis of Transmembrane Domain of Amyloid Precursor Protein: Successive Tri- and Tetrapeptide Release in Amyloidβ-Protein Production. International Journal of Alzheimer s Disease. 2012. 1–7. 22 indexed citations

Kakuda, Nobuto, Mikio Shoji, Hiroyuki Arai, et al.. (2012). Altered γ‐secretase activity in mild cognitive impairment and Alzheimer's disease. EMBO Molecular Medicine. 4(4). 344–352. 49 indexed citations

Takami, Mako, Yu Nagashima, Y Sano, et al.. (2009). γ-Secretase: Successive Tripeptide and Tetrapeptide Release from the Transmembrane Domain of β-Carboxyl Terminal Fragment. Journal of Neuroscience. 29(41). 13042–13052. 404 indexed citations

Kakuda, Nobuto, Satoru Funamoto, Mako Takami, et al.. (2006). Equimolar Production of Amyloid β-Protein and Amyloid Precursor Protein Intracellular Domain from β-Carboxyl-terminal Fragment by γ-Secretase. Journal of Biological Chemistry. 281(21). 14776–14786. 131 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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