R Hanada

478 citations
8 papers · 352 · h-index 7

Impact in

  • Hematology top 5%
    • Autoimmune and Inflammatory Disorders Research
    • Acute Myeloid Leukemia Research
    • Chronic Myeloid Leukemia Treatments
    • Immune Cell Function and Interaction

Papers in

R Hanada

8 papers receiving 346 citations

Peers

R Hanada
Comparison fields: 5 of 31
  • Hematology 199
  • Immunology 99
  • Infectious Diseases 86
  • Oncology 109
  • Neurology 43
Replace B M Camitta with:
B M Camitta United States
Olga Militano United States
Monika Trebo Austria
Frank Rothmann Germany
Ikuo Miura Japan
Yasutaka Aoyama Japan
Lauren Pommert United States
Xinan Cen China
Bachar Samra United States
R Hanada relative to B M Camitta United States B M Camitta's profile →
Citations per field
00.5×3.6×
B M Camitta · 1×
Citations per year

Countries citing papers authored by R Hanada

Since Specialization
Citations

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

Fields of papers citing papers by R Hanada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

8 of 8 papers shown
#Work
1 1993161
2 200146
3
Clinical significance of TAL1 gene alteration in childhood T-cell acute lymphoblastic leukemia and lymphoma.
199345
4
Karyotypic patterns in acute mixed lineage leukemia.
199036
5 200428
6
Homozygous deletions of p16/MTS1 and p15/MTS2 genes are frequent in t(1;19)-negative but not in t(1;19)-positive B precursor acute lymphoblastic leukemia in childhood.
199619
7 199116
8
[Alterations of the p53 gene and clinical features in childhood acute lymphoblastic leukemia].
19971

About R Hanada

R Hanada is a scholar working on Molecular Biology, Genetics, Neurology, Oncology and Epidemiology, having authored 8 papers that have together received 352 indexed citations. Recurring topics across this work include Chronic Lymphocytic Leukemia Research (2 papers), Acute Lymphoblastic Leukemia research (2 papers), Neuroblastoma Research and Treatments (2 papers), Cytomegalovirus and herpesvirus research (1 paper), Chronic Myeloid Leukemia Treatments (1 paper), Pancreatic and Hepatic Oncology Research (1 paper), Acute Myeloid Leukemia Research (1 paper) and T-cell and Retrovirus Studies (1 paper). The work is most often cited by research in Hematology (199 citations), Immunology (99 citations), Infectious Diseases (86 citations), Oncology (109 citations) and Neurology (43 citations). R Hanada has collaborated with scholars based in Japan, United Kingdom and Germany. Frequent co-authors include Toshiyuki Miyashita, Masahiro Asada, Gerald Niedobitek, M Sakurai, Hermann Herbst, Hiroshi Kawaguchi, Masahiro Tsuchida, Akihiro Kinoshita, Noritada Kobayashi and Keiko Yamamoto. Their work appears in journals such as Journal of Clinical Investigation, British Journal of Haematology, Surgical Endoscopy, Pediatric Surgery International and PubMed.

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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