Tina Green

2.5k citations
31 papers · 1.3k indexed · 1 hit paper · h-index 14
Topics
Chronic Lymphocytic Leukemia Research (6 papers)Cervical Cancer and HPV Research (5 papers)Lymphoma Diagnosis and Treatment (5 papers)

In The Last Decade

Tina Green

30 papers receiving 1.3k citations

Hit Papers

Immunohistochemical Double-Hit Score Is a Strong Predicto...20122026201620212012100200300400

Peers

Tina Green
Comparison fields: 5 of 71
  • Pathology and Forensic Medicine 577
  • Epidemiology 479
  • Oncology 419
  • Genetics 325
  • Immunology 215
Replace Laura Caggiari with:
Laura Caggiari Italy
Ivy Sng Singapore
Natasha Jiwa Netherlands
JP Clauvel France
Thierry Guillaume France
E. Beth United States
Peter von Wussow Germany
Gwendolin Muehlinghaus Germany
Rex Au-Yeung Hong Kong
David Liebowitz United States
Tina Green relative to Laura Caggiari Italy Laura Caggiari's profile →
Citations per field
00.5×2.6×
Laura Caggiari · 1×
Citations per year

Countries citing papers authored by Tina Green

Since Specialization
Citations

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

Fields of papers citing papers by Tina Green

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tina Green

This figure shows the co-authorship network connecting the top 25 collaborators of Tina Green. A scholar is included among the top collaborators of Tina Green 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 Tina Green. Tina Green is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 1
3 3
4 8
5 14
6 36
7 56
8 3
9 112
10
Immunohistochemical Double-Hit Score Is a Strong Predictor of Outcome in Patients With Diffuse Large B-Cell Lymphoma Treated With Rituximab Plus Cyclophosphamide, Doxorubicin, Vincristine, and Prednisonebreakdown →
481
11
Diffuse Large B-Cell Lymphoma: Expression patterns of Cdc6 and its correlation with subtypes, Ki67 and structural changes of the INK4/ARF locus
1
12 55
13 10
14 69
15 16
16 42
17 204
18 24
19 3
20 5

About Tina Green

Tina Green is a scholar working on Genetics, Pathology and Forensic Medicine and Epidemiology, having authored 31 papers that have together received 1.3k indexed citations. Recurring topics across this work include Chronic Lymphocytic Leukemia Research (6 papers), Cervical Cancer and HPV Research (5 papers) and Lymphoma Diagnosis and Treatment (5 papers). The work is most often cited by research in Pathology and Forensic Medicine (577 citations), Genetics (325 citations) and Oncology (419 citations). Tina Green has collaborated with scholars based in United States, United Kingdom and Denmark. Frequent co-authors include Michael Møller, Ken H. Young, Zijun Y. Xu‐Monette, Ole Nielsen, Joseph M. Antonello, Carlo Visco, Attilio Orazi, Mikael Frederiksen, Ronald S. Go and Ole Gadeberg. Their work appears in journals such as Journal of Clinical Oncology, Blood and PLoS ONE.

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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