Gemma L. Kelly

8.1k citations
59 papers · 4.2k indexed · 2 hit papers · h-index 30
Topics
Viral-associated cancers and disorders (19 papers)Cancer-related Molecular Pathways (18 papers)Lymphoma Diagnosis and Treatment (17 papers)

In The Last Decade

Gemma L. Kelly

56 papers receiving 4.2k citations

Hit Papers

How does p53 induce apoptosis and how does this relate to...2017202620202023201720222505007501000

Peers

Gemma L. Kelly
Comparison fields: 5 of 119
  • Molecular Biology 2.3k
  • Oncology 1.9k
  • Pathology and Forensic Medicine 837
  • Immunology 700
  • Cancer Research 635
Replace Xiaoling Song with:
Xiaoling Song China
Seong‐Jin Kim South Korea
Adly Yacoub United States
Elaine M. Hurt United States
Priscilla N. Kelly Australia
Min H. Kang United States
Guang Peng United States
Kaoru Kiguchi United States
Andrei L. Gartel United States
Gemma L. Kelly relative to Xiaoling Song China Xiaoling Song's profile →
Citations per field
00.5×1.5×2.1×
Xiaoling Song · 1×
Citations per year

Countries citing papers authored by Gemma L. Kelly

Since Specialization
Citations

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

Fields of papers citing papers by Gemma L. Kelly

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gemma L. Kelly. 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 Gemma L. Kelly. The network helps show where Gemma L. Kelly may publish in the future.

Co-authorship network of co-authors of Gemma L. Kelly

This figure shows the co-authorship network connecting the top 25 collaborators of Gemma L. Kelly. A scholar is included among the top collaborators of Gemma L. Kelly 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 Gemma L. Kelly. Gemma L. Kelly 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 7
2 25
3 4
4 14
5
BCL-2 protein family: attractive targets for cancer therapybreakdown →
255
6 17
7 220
8 2
9 66
10 231
11 18
12
How does p53 induce apoptosis and how does this relate to p53-mediated tumour suppression?breakdown →
1007
13 18
14 34
15 25
16 29
17 126
18 76
19 78
20 71

About Gemma L. Kelly

Gemma L. Kelly is a scholar working on Oncology, Pathology and Forensic Medicine and Genetics, having authored 59 papers that have together received 4.2k indexed citations. Recurring topics across this work include Viral-associated cancers and disorders (19 papers), Cancer-related Molecular Pathways (18 papers) and Lymphoma Diagnosis and Treatment (17 papers). The work is most often cited by research in Oncology (1.9k citations), Pathology and Forensic Medicine (837 citations) and Cancer Research (635 citations). Gemma L. Kelly has collaborated with scholars based in Australia, United Kingdom and United States. Frequent co-authors include Andreas Strasser, Brandon J. Aubrey, Marco J. Herold, Ana Janic, Alan B. Rickinson, Andrew Bell, Sarah T. Diepstraten, Guillaume Lessène, Deeksha Kaloni and Martin Rowe. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Medicine and Genes & Development.

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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