Hitoshi Ichikawa

9.6k citations
143 papers · 5.0k · h-index 42

Impact in

Papers in

Hitoshi Ichikawa

137 papers receiving 4.9k citations

Peers

Hitoshi Ichikawa
Comparison fields: 5 of 127
  • Hematology 749
  • Cancer Research 690
  • Oncology 1.0k
  • Molecular Biology 2.7k
  • Pulmonary and Respiratory Medicine 1.1k
Replace Yan W. Asmann with:
Yan W. Asmann United States
Dennis K. Watson United States
Angela Greco Italy
Takao Takahashi Japan
Neil V. Morgan United Kingdom
Shuki Mizutani Japan
Chao Lü United States
Michael A. Rieger Germany
Paul‐Henri Roméo France
Carl‐Henrik Heldin Sweden
Hitoshi Ichikawa relative to Yan W. Asmann United States Yan W. Asmann's profile →
Citations per field
00.5×1.5×1.8×
Yan W. Asmann · 1×
Citations per year

Countries citing papers authored by Hitoshi Ichikawa

Since Specialization
Citations

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

Fields of papers citing papers by Hitoshi Ichikawa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Hitoshi Ichikawa, 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 Hitoshi Ichikawa Line = papers co-authored together Hitoshi Ichikawa links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 143 papers — load more, or switch the sort, to bring in the rest.

#Work
1
An RNA-binding protein gene, TLS/FUS, is fused to ERG in human myeloid leukemia with t(16;21) chromosomal translocation.
1994197
2 2009187
3 2006167
4 2017161
5 2019161
6 2010150
7 1993125
8 2007118
9 2006113
10 1997107
11 200897
12 200687
13 200986
14 201883
15 199881
16 200080
17 200875
18 201371
19 200867
20 199766

About Hitoshi Ichikawa

Hitoshi Ichikawa is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Hematology, Oncology and Cancer Research, having authored 143 papers that have together received 5.0k indexed citations. Recurring topics across this work include Sarcoma Diagnosis and Treatment (28 papers), Acute Myeloid Leukemia Research (24 papers), Cancer Genomics and Diagnostics (12 papers), Epigenetics and DNA Methylation (11 papers), Cancer-related gene regulation (8 papers), Cancer-related molecular mechanisms research (7 papers), Genomics and Chromatin Dynamics (7 papers) and Lung Cancer Treatments and Mutations (7 papers). The work is most often cited by research in Hematology (749 citations), Cancer Research (690 citations), Oncology (1.0k citations), Molecular Biology (2.7k citations) and Pulmonary and Respiratory Medicine (1.1k citations). Hitoshi Ichikawa has collaborated with scholars based in Japan, United Kingdom and United States. Frequent co-authors include Misao Ohki, Akira Kawai, Akihiko Yoshida, Y Hayashi, Atsushi Iwama, Tsutomu Ohta, Issay Kitabayashi, Gary S. Goldberg, Yongquan Shen and Yoichi Taya. Their work appears in journals such as Cancer Science, Modern Pathology, Genes Chromosomes and Cancer, Journal of Clinical Oncology and Scientific Reports.

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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