Takeshi Corpora

11 total papers · 454 total citations
9 papers, 349 citations indexed

About

Takeshi Corpora is a scholar working on Hematology, Molecular Biology and Genetics. According to data from OpenAlex, Takeshi Corpora has authored 9 papers receiving a total of 349 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Hematology, 7 papers in Molecular Biology and 2 papers in Genetics. Recurrent topics in Takeshi Corpora's work include Acute Myeloid Leukemia Research (8 papers), Ubiquitin and proteasome pathways (1 paper) and Cancer-related gene regulation (1 paper). Takeshi Corpora is often cited by papers focused on Acute Myeloid Leukemia Research (8 papers), Ubiquitin and proteasome pathways (1 paper) and Cancer-related gene regulation (1 paper). Takeshi Corpora collaborates with scholars based in United States, United Kingdom and Singapore. Takeshi Corpora's co-authors include John H. Bushweller, Nancy A. Speck, Liya Roudaia, Yunpeng Zhou, Miki Newman, Jiangli Yan, Christina Matheny, Jerónimo Bravo, Peiqing Liu and Ting-Lei Gu and has published in prestigious journals such as Journal of Biological Chemistry, The EMBO Journal and Blood.

In The Last Decade

Takeshi Corpora

9 papers receiving 347 citations

Author Peers

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

Author Last Decade Papers Cites
Takeshi Corpora 267 193 52 28 27 9 349
Cynthia K. Hahn 247 0.9× 109 0.6× 82 1.6× 53 1.9× 11 0.4× 11 365
John Nechtman 220 0.8× 104 0.5× 119 2.3× 42 1.5× 10 0.4× 14 399
David A. Bateman 199 0.7× 61 0.3× 21 0.4× 57 2.0× 22 0.8× 9 377
Naïs Prade-Houdellier 268 1.0× 147 0.8× 58 1.1× 66 2.4× 5 0.2× 6 389
Stela Álvarez-Fernández 216 0.8× 118 0.6× 49 0.9× 83 3.0× 13 0.5× 11 363
Jennifer M. Weber 171 0.6× 101 0.5× 56 1.1× 87 3.1× 31 1.1× 9 379
Mandy Mayo Aust 289 1.1× 95 0.5× 49 0.9× 79 2.8× 6 0.2× 7 370
Anthony C. Bishop 257 1.0× 37 0.2× 32 0.6× 54 1.9× 23 0.9× 11 390
Chinmay Munje 186 0.7× 145 0.8× 44 0.8× 39 1.4× 5 0.2× 11 322
Mairead Young 238 0.9× 79 0.4× 53 1.0× 86 3.1× 23 0.9× 8 398

Countries citing papers authored by Takeshi Corpora

Since Specialization
Citations

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

Fields of papers citing papers by Takeshi Corpora

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Takeshi Corpora

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