Ichiro Mori

198 papers receiving 5.5k citations

Peers

Ichiro Mori
Comparison fields: 5 of 154
  • Oncology 1.2k
  • Endocrinology, Diabetes and Metabolism 651
  • Nephrology 276
  • Cancer Research 565
  • Molecular Biology 2.2k
Replace Takashi Joh with:
Takashi Joh Japan
Sohita Dhillon New Zealand
Anthony Markham New Zealand
Lin Leng United States
Ferdinando Nicoletti Italy
Bysani Chandrasekar United States
Erik A.L. Biessen Netherlands
Gérard Feldmann France
M. Zabel Poland
Johan Kuiper Netherlands
Ichiro Mori relative to Takashi Joh Japan Takashi Joh's profile →
Citations per field
00.5×1.7×
Takashi Joh · 1×
Citations per year

Countries citing papers authored by Ichiro Mori

Since Specialization
Citations

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

Fields of papers citing papers by Ichiro Mori

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ichiro Mori, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ichiro Mori Line = papers co-authored together Ichiro Mori links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 203 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002225
2 1998194
3 2007190
4 1998181
5 2005163
6 1998130
7 2000130
8 2002112
9
Prognostic significance of vascular endothelial growth factor D in breast carcinoma with long-term follow-up.
2003110
10 2019101
11 2009100
12
Urokinase-type plasminogen activator system and breast cancer (Review).
200594
13 200192
14 201290
15 200989
16 200287
17 199085
18 201479
19 200177
20 198377

About Ichiro Mori

Ichiro Mori is a scholar working on Molecular Biology, Oncology, Epidemiology, Endocrinology, Diabetes and Metabolism and Cancer Research, having authored 203 papers that have together received 5.6k indexed citations. Recurring topics across this work include Thyroid Cancer Diagnosis and Treatment (15 papers), Breast Cancer Treatment Studies (12 papers), AI in cancer detection (9 papers), Neuroendocrine Tumor Research Advances (9 papers), Angiogenesis and VEGF in Cancer (8 papers), Adipose Tissue and Metabolism (8 papers), Breast Lesions and Carcinomas (8 papers) and Heme Oxygenase-1 and Carbon Monoxide (8 papers). The work is most often cited by research in Oncology (1.2k citations), Endocrinology, Diabetes and Metabolism (651 citations), Nephrology (276 citations), Cancer Research (565 citations) and Molecular Biology (2.2k citations). Ichiro Mori has collaborated with scholars based in Japan, China and United States. Frequent co-authors include Kennichi Kakudo, Misa Nakamura, Yasushi Nakamura, Amy M. Gehring, Qifeng Yang, Christopher T. Walsh, Nobukazu Ishizaka, Ryozo Nagai, Minoru Ohno and Emiko Taniguchi. Their work appears in journals such as Pathology International, Modern Pathology, Hypertension, Biochemical and Biophysical Research Communications and Breast Cancer Research and Treatment.

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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