Kenji Tada

2.1k total citations · 1 hit paper
23 papers, 1.7k citations indexed

About

Kenji Tada is a scholar working on Genetics, Molecular Biology and Surgery. According to data from OpenAlex, Kenji Tada has authored 23 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Genetics, 7 papers in Molecular Biology and 6 papers in Surgery. Recurrent topics in Kenji Tada's work include Glioma Diagnosis and Treatment (7 papers), Microtubule and mitosis dynamics (3 papers) and Epigenetics and DNA Methylation (2 papers). Kenji Tada is often cited by papers focused on Glioma Diagnosis and Treatment (7 papers), Microtubule and mitosis dynamics (3 papers) and Epigenetics and DNA Methylation (2 papers). Kenji Tada collaborates with scholars based in Japan, United States and Hong Kong. Kenji Tada's co-authors include Yukitaka Ushio, Masato Kochi, Takeshi Sakuno, Yoshinori Watanabe, Hideyuki Saya, Shoji Shiraishi, Hideo Nakamura, Naoki Shinojima, Takanori Kamiryo and Jun‐ichi Kuratsu and has published in prestigious journals such as Nature, The Journal of Cell Biology and Cancer.

In The Last Decade

Kenji Tada

22 papers receiving 1.7k citations

Hit Papers

Prognostic value of epidermal growth factor receptor in p... 2003 2026 2010 2018 2003 100 200 300 400 500
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Prognostic value of epidermal growth factor receptor in patients with glioblastoma multiforme.
    2003 536 citations Naoki Shinojima, Kenji Tada et al. PubMed profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kenji Tada Japan 15 829 639 347 319 284 23 1.7k
Nathalie Baeza France 17 1.2k 1.4× 887 1.4× 179 0.5× 561 1.8× 431 1.5× 28 2.2k
Bárbara Meléndez Spain 22 859 1.0× 442 0.7× 157 0.5× 421 1.3× 439 1.5× 66 1.6k
Griffith Harsh United States 18 742 0.9× 302 0.5× 126 0.4× 231 0.7× 273 1.0× 36 1.8k
Lori Frederick United States 15 1.1k 1.3× 646 1.0× 107 0.3× 287 0.9× 523 1.8× 22 1.7k
Lucie Karayan‐Tapon France 23 794 1.0× 603 0.9× 115 0.3× 524 1.6× 467 1.6× 61 1.6k
Britta Blaschke Germany 14 904 1.1× 655 1.0× 78 0.2× 306 1.0× 219 0.8× 15 1.5k
José M. de Campos Spain 30 985 1.2× 867 1.4× 129 0.4× 514 1.6× 274 1.0× 77 2.3k
Daisuke Kita Japan 18 459 0.6× 340 0.5× 90 0.3× 248 0.8× 159 0.6× 53 1.1k
David Tran United States 20 528 0.6× 568 0.9× 148 0.4× 255 0.8× 485 1.7× 39 1.4k
André O. von Bueren Germany 28 1.2k 1.4× 1.4k 2.2× 90 0.3× 283 0.9× 253 0.9× 111 2.3k

Countries citing papers authored by Kenji Tada

Since Specialization
Citations

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

Fields of papers citing papers by Kenji Tada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kenji Tada

This figure shows the co-authorship network connecting the top 25 collaborators of Kenji Tada. A scholar is included among the top collaborators of Kenji Tada 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 Kenji Tada. Kenji Tada 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.
2.
Tada, Kenji, et al.. (2011). Visual Characteristics of Colored LED Lights In Dense Fog. 35. 134–135.
3.
Tada, Kenji, et al.. (2011). Condensin association with histone H2A shapes mitotic chromosomes. Nature. 474(7352). 477–483. 150 indexed citations
4.
Ono, Masayoshi, Shunsuke Ohnishi, Kimitoshi Kubo, et al.. (2010). [Repetition of Helicobacter cinaedi infections during chemotherapy for malignant lymphoma].. PubMed. 51(12). 1781–5. 2 indexed citations
5.
Sakuno, Takeshi, Kenji Tada, & Yoshinori Watanabe. (2009). Kinetochore geometry defined by cohesion within the centromere. Nature. 458(7240). 852–858. 135 indexed citations
6.
7.
Levin, Victor A., et al.. (2006). Lysate array analyses of signal transduction inhibitors in tumor cell lines. Clinical Proteomics. 2(1-2). 33–43. 2 indexed citations
8.
Shinojima, Naoki, Masato Kochi, Jun-ichiro Hamada, et al.. (2004). The influence of sex and the presence of giant cells on postoperative long-term survival in adult patients with supratentorial glioblastoma multiforme. Journal of neurosurgery. 101(2). 219–226. 81 indexed citations
9.
10.
Tada, Kenji, Masato Kochi, Hideyuki Saya, et al.. (2003). Preliminary observations on genetic alterations in pilocytic astrocytomasassociated with neurofibromatosis 1. Neuro-Oncology. 5(4). 228–234. 30 indexed citations
11.
Shiraishi, Shoji, Kenji Tada, Hideo Nakamura, et al.. (2002). Influence of p53 mutations on prognosis of patients with glioblastoma. Cancer. 95(2). 249–257. 74 indexed citations
12.
Kamiryo, Takanori, Kenji Tada, Shoji Shiraishi, et al.. (2002). Analysis of homozygous deletion of the p16 gene and correlation with survival in patients with glioblastoma multiforme. Journal of neurosurgery. 96(5). 815–822. 39 indexed citations
13.
Kondo, Tatsuya, Tomoaki Murata, Thomas A. Ebersole, et al.. (2002). Expression of Hqk Encoding a KH RNA Binding Protein Is Altered in Human Glioma. Japanese Journal of Cancer Research. 93(2). 167–177. 50 indexed citations
14.
Tada, Kenji, Shoji Shiraishi, Takanori Kamiryo, et al.. (2001). Analysis of loss of heterozygosity for chromosome 10 in patients with malignant astrocytic tumors: correlation with patient age and survival. Journal of neurosurgery. 95(4). 651–659. 60 indexed citations
15.
Hirota, Toru, Tetsuro Morisaki, Yasuyuki Nishiyama, et al.. (2000). Zyxin, a Regulator of Actin Filament Assembly, Targets the Mitotic Apparatus by Interacting with H-Warts/Lats1 Tumor Suppressor. The Journal of Cell Biology. 149(5). 1073–1086. 168 indexed citations
16.
Kochi, Masato, Tomoaki Goto, Toru Nishi, et al.. (2000). Randomized Comparison of Intra-arterial Versus Intravenous Infusion of ACNU for Newly Diagnosed Patients with Glioblastoma. Journal of Neuro-Oncology. 49(1). 63–70. 32 indexed citations
17.
Nishi, Toru, Tomoaki Goto, Hideo Takeshima, et al.. (1999). Tissue factor expressed in pituitary adenoma cells contributes to the development of vascular events in pituitary adenomas. Cancer. 86(7). 1354–1361. 10 indexed citations
18.
Matsuda, Yasutaka, Kenji Tada, Atsushi Yasuda, et al.. (1991). Increased MR signal intensity due to cervical myelopathy. Journal of neurosurgery. 74(6). 887–892. 156 indexed citations
19.
Takahashi, Hiroshi, Takao Yamamuro, Hideo Okumura, Ryuichi Kasai, & Kenji Tada. (1990). Bone blood flow after spinal paralysis in the rat. Journal of Orthopaedic Research®. 8(3). 393–400. 14 indexed citations
20.

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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