Tin Han

100 papers receiving 2.1k citations

Peers

Tin Han
Comparison fields: 5 of 77
  • Genetics 780
  • Pathology and Forensic Medicine 458
  • Immunology 487
  • Hematology 266
  • Biochemistry 85
Replace Albert K. W. Lie with:
Albert K. W. Lie China
Hirokazu Murakami Japan
Karl‐Walter Sykora Germany
G Souillet France
Hamid A B Al-Mondhiry United States
M Harada Japan
Mikaël Roussel France
Makoto Hirokawa Japan
Daniel Espinouse France
Takayuki Saitoh Japan
Tin Han relative to Albert K. W. Lie China Albert K. W. Lie's profile →
Citations per field
00.5×2×4×6.6×
Albert K. W. Lie · 1×
Citations per year

Countries citing papers authored by Tin Han

Since Specialization
Citations

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

Fields of papers citing papers by Tin Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 100 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1987211
2 1984142
3 1973128
4
Whole-blood culture technique for functional studies of lymphocyte reactivity to mitogens, antigens, and homologous lymphocytes.
1973120
5 1970110
6 1966106
7 1967104
8 197295
9 197481
10 197952
11 199052
12 198048
13 198245
14 196744
15
Prognostic significance of karyotypic abnormalities in B cell chronic lymphocytic leukemia: an update.
198740
16 198237
17 197236
18 197135
19 197933
20 197329

About Tin Han

Tin Han is a scholar working on Genetics, Pathology and Forensic Medicine, Immunology, Hematology and Oncology, having authored 100 papers that have together received 2.6k indexed citations. Recurring topics across this work include Chronic Lymphocytic Leukemia Research (37 papers), Lymphoma Diagnosis and Treatment (30 papers), T-cell and B-cell Immunology (16 papers), Immunotherapy and Immune Responses (11 papers), Acute Myeloid Leukemia Research (8 papers), Acute Lymphoblastic Leukemia research (7 papers), Cancer, Stress, Anesthesia, and Immune Response (4 papers) and Viral-associated cancers and disorders (3 papers). The work is most often cited by research in Genetics (780 citations), Pathology and Forensic Medicine (458 citations), Immunology (487 citations), Hematology (266 citations) and Biochemistry (85 citations). Tin Han has collaborated with scholars based in United States, Germany and Italy. Frequent co-authors include Joseph E. Sokal, Hiroshi Takita, Jun Minowada, Edward S. Henderson, Germán A. Gómez, Maurice P Barcos, Avery A. Sandberg, Naoki Sadamori, B Dadey and John L. Pauly. Their work appears in journals such as Cancer, Journal of Surgical Oncology, New England Journal of Medicine, JNCI Journal of the National Cancer Institute and The American Journal of Medicine.

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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