Janelle Sharkey
- Physiology top 0.5%
- Adenosine and Purinergic Signaling 1
- Immunology top 5%
- Immunotherapy and Immune Responses 8
- Immune Cell Function and Interaction 8
- T-cell and B-cell Immunology 4
- Immune Response and Inflammation 2
- Oncology top 5%
- CAR-T cell therapy research 6
- Clinical Biochemistry top 10%
- Ophthalmology top 5%
-
- Cell death mechanisms and regulation 3
- Protein Kinase Regulation and GTPase Signaling 1
- Co-authors
- Mark J. SmythNicole M. McLaughlinSandra PommeyJohn StaggDelphine DenoyerKaren M. DwyerUpulie DivisekeraJeremy B. Swann
- Cited by
- PhysiologyImmunologyOncology
- Journals
- Proceedings of the National Academy of Sciences (4 papers)Blood (3 papers)Cancer Research (3 papers)
- Partner nations
- AustraliaJapanUnited States
In The Last Decade
Janelle Sharkey
18 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 77
- Physiology 323
- Immunology 702
- Oncology 549
- Clinical Biochemistry 69
- Ophthalmology 64
Countries citing papers authored by Janelle Sharkey
This map shows the geographic impact of Janelle Sharkey'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 Janelle Sharkey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Janelle Sharkey more than expected).
Fields of papers citing papers by Janelle Sharkey
This network shows the impact of papers produced by Janelle Sharkey. 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 Janelle Sharkey. The network helps show where Janelle Sharkey may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Janelle Sharkey, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 13 | |
| 2 | 2010 | 58 | |
| 3 | 2010 | 25 | |
| 4 | Anti-CD73 antibody therapy inhibits breast tumor growth and metastasisbreakdown → | 2010 | 479 |
| 5 | 2009 | 20 | |
| 6 | 2009 | 18 | |
| 7 | 2009 | 21 | |
| 8 | 2009 | 87 | |
| 9 | 2008 | 23 | |
| 10 | 2008 | 244 | |
| 11 | Cancer immunoediting: Recent progress in elimination and equilibrium | 2008 | 1 |
| 12 | 2008 | 40 | |
| 13 | 2008 | 118 | |
| 14 | 2007 | 55 | |
| 15 | 2006 | 18 | |
| 16 | 2005 | 1 | |
| 17 | Advanced glycation end products in vitreous: Structural and functional implications for diabetic vitreopathy. | 1998 | 108 |
| 18 | 1993 | 29 |
About Janelle Sharkey
Janelle Sharkey is a scholar working on Immunology, Transplantation and Oncology, having authored 18 papers that have together received 1.4k indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (8 papers), Immune Cell Function and Interaction (8 papers), CAR-T cell therapy research (6 papers), T-cell and B-cell Immunology (4 papers), Cell death mechanisms and regulation (3 papers), Immune Response and Inflammation (2 papers), Adenosine and Purinergic Signaling (1 paper) and Protein Kinase Regulation and GTPase Signaling (1 paper). The work is most often cited by research in Physiology (323 citations), Immunology (702 citations) and Oncology (549 citations). Janelle Sharkey has collaborated with scholars based in Australia, Japan and United States. Frequent co-authors include Mark J. Smyth, Nicole M. McLaughlin, Sandra Pommey, John Stagg, Delphine Denoyer, Karen M. Dwyer, Upulie Divisekera, Jeremy B. Swann, Anabel Silva and Matthew D. Vesely. Their work appears in journals such as Proceedings of the National Academy of Sciences, Blood, Cancer Research, The Journal of Immunology and Clinical Cancer Research.
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.