Kate Connor

588 citations
16 papers · 135 · h-index 7

Impact in

    • Glioma Diagnosis and Treatment
    • Cancer, Hypoxia, and Metabolism
    • Cancer Genomics and Diagnostics
    • MicroRNA in disease regulation

Papers in

Kate Connor

16 papers receiving 134 citations

Peers

Kate Connor
Comparison fields: 5 of 45
  • Genetics 35
  • Cancer Research 34
  • Structural Biology 2
  • Molecular Biology 56
  • Oncology 20
Replace Monika A. Jarzabek with:
Monika A. Jarzabek Ireland
Sean Mizzi Malta
Alice C. O’Farrell Ireland
Alison D. Parisian United States
Tamrin Chowdhury South Korea
Álvaro Curiel‐García United States
Dennis S. Metselaar Netherlands
Elke Pfaff Germany
Jianhui Ma United States
Yangong Zhang China
Kate Connor relative to Monika A. Jarzabek Ireland Monika A. Jarzabek's profile →
Citations per field
00.5×
Monika A. Jarzabek · 1×
Citations per year

Countries citing papers authored by Kate Connor

Since Specialization
Citations

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

Fields of papers citing papers by Kate Connor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 202038
2 201815
3 202414
4 201712
5 201911
6 202210
7 20199
8 20196
9 20204
10 20243
11 20173
12 20223
13 20242
14 20232
15 20242
16 20201

About Kate Connor

Kate Connor is a scholar working on Molecular Biology, Genetics, Cancer Research, Oncology and Radiology, Nuclear Medicine and Imaging, having authored 16 papers that have together received 135 indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (5 papers), Cancer Genomics and Diagnostics (4 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Ferroptosis and cancer prognosis (1 paper), Heat shock proteins research (1 paper), BRCA gene mutations in cancer (1 paper), Medical Imaging Techniques and Applications (1 paper) and Nanoparticle-Based Drug Delivery (1 paper). The work is most often cited by research in Genetics (35 citations), Cancer Research (34 citations), Structural Biology (2 citations), Molecular Biology (56 citations) and Oncology (20 citations). Kate Connor has collaborated with scholars based in Ireland, Netherlands and France. Frequent co-authors include Annette T. Byrne, Anna Golebiewska, Jochen H.M. Prehn, William M. Gallagher, Alice C. O’Farrell, Kieron J. Sweeney, Ian S. Miller, Emer Conroy, Markus Rehm and Maïté Verreault. Their work appears in journals such as Scientific Reports, Oncotarget, American Journal of Community Psychology, Neuro-Oncology and Drug Delivery and Translational 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.

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