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.
CD13 is a therapeutic target in human liver cancer stem cells
2010501 citationsNaotsugu Haraguchi, Hideshi Ishii et al.Journal of Clinical Investigationprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Daisuke Takiuchi
Since
Specialization
Citations
This map shows the geographic impact of Daisuke Takiuchi'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 Daisuke Takiuchi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daisuke Takiuchi more than expected).
Fields of papers citing papers by Daisuke Takiuchi
This network shows the impact of papers produced by Daisuke Takiuchi. 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 Daisuke Takiuchi. The network helps show where Daisuke Takiuchi may publish in the future.
Co-authorship network of co-authors of Daisuke Takiuchi
This figure shows the co-authorship network connecting the top 25 collaborators of Daisuke Takiuchi.
A scholar is included among the top collaborators of Daisuke Takiuchi 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 Daisuke Takiuchi. Daisuke Takiuchi is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Morimoto, Osakuni, Satoshi Eguchi, Noriko Wada, et al.. (2019). [A Case Report of Long Survival in Pancreatic Cancer with Superior Mesenteric Arterial Invasion Following Multimodal Therapy].. PubMed. 46(13). 2342–2344.1 indexed citations
8.
Takiuchi, Daisuke, Osakuni Morimoto, Satoshi Eguchi, et al.. (2019). [A Case of Chemotherapy with Abscess Drainage for Pancreatic Cancer Detected Due to Peritonitis].. PubMed. 46(13). 2458–2460.1 indexed citations
9.
Wada, Noriko, Yusuke Akamaru, Koji Munakata, et al.. (2019). [Adjuvant Chemotherapy and the Prognosis of ypStageⅠ Gastric Cancer].. PubMed. 46(1). 85–87.1 indexed citations
Takiuchi, Daisuke, Osakuni Morimoto, Noriko Wada, et al.. (2017). [A Case of Urothelial Carcinoma Who Underwent Pancreaticoduodenectomy and Was Diagnosed with Groove Pancreatitis and Preoperatively Suffered from Duodenal Stenosis].. PubMed. 44(12). 2003–2005.4 indexed citations
12.
Akamaru, Yusuke, Noriko Wada, Takafumi Hirao, et al.. (2017). [A Case of Alpha-Fetoprotein-Producing Gastric Cancer with Synchronous Liver Metastasis Achieving Recurrence-Free Survival for Five Years by Gastrectomy, Hepatectomy, and Adjuvant Chemotherapy].. PubMed. 44(12). 1775–1777.1 indexed citations
13.
Kubo, Masahiko, Kei Asukai, Kozo Noguchi, et al.. (2013). [Response to neoadjuvant chemotherapy in breast cancer as assessed by subtype].. PubMed. 40(12). 1653–5.1 indexed citations
Haraguchi, Naotsugu, Hideshi Ishii, Koshi Mimori, et al.. (2010). CD13 is a therapeutic target in human liver cancer stem cells. Journal of Clinical Investigation. 120(9). 3326–3339.501 indexed citations breakdown →
Miki, Hirofumi, Shigeyuki Tamura, Hiroshi Wada, et al.. (2003). [A case of gastric cancer with peritoneal dissemination which showed the intraperitoneal CR by administrating TS-1 orally and paclitaxel intraperitoneally].. PubMed. 30(11). 1661–4.1 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.