Christopher J. LaRocca

903 citations
33 papers · 527 · h-index 11

Impact in

  • Oncology top 10%
    • CAR-T cell therapy research
    • Cancer Immunotherapy and Biomarkers
  • Genetics top 10%
    • Virus-based gene therapy research

Papers in

    • CAR-T cell therapy research 9
    • Pancreatic and Hepatic Oncology Research 3
    • Cutaneous Melanoma Detection and Management 1
    • Virus-based gene therapy research 15

Christopher J. LaRocca

31 papers receiving 522 citations

Peers

Christopher J. LaRocca
Comparison fields: 5 of 59
  • Oncology 303
  • Genetics 271
  • Biotechnology 67
  • Immunology 95
  • Health Informatics 3
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Citations per field
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Citations per year

Countries citing papers authored by Christopher J. LaRocca

Since Specialization
Citations

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

Fields of papers citing papers by Christopher J. LaRocca

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christopher J. LaRocca. 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 Christopher J. LaRocca. The network helps show where Christopher J. LaRocca may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019123
2 2018110
3 202149
4 201543
5 202036
6 201830
7 201815
8 201814
9 202014
10 201613
11 201610
12 202110
13 202110
14 20228
15 20217
16 20217
17 20164
18 20243
19 20203
20 20223

About Christopher J. LaRocca

Christopher J. LaRocca is a scholar working on Oncology, Genetics, Biotechnology, Surgery and Molecular Biology, having authored 33 papers that have together received 527 indexed citations. Recurring topics across this work include Virus-based gene therapy research (15 papers), CAR-T cell therapy research (9 papers), Cancer Research and Treatments (7 papers), Viral Infectious Diseases and Gene Expression in Insects (3 papers), Pancreatic and Hepatic Oncology Research (3 papers), Hepatocellular Carcinoma Treatment and Prognosis (2 papers), Surgical Simulation and Training (1 paper) and Cutaneous Melanoma Detection and Management (1 paper). The work is most often cited by research in Oncology (303 citations), Genetics (271 citations), Biotechnology (67 citations), Immunology (95 citations) and Health Informatics (3 citations). Christopher J. LaRocca has collaborated with scholars based in United States, Japan and United Kingdom. Frequent co-authors include Susanne G. Warner, Yuman Fong, Masato Yamamoto, Nanhai G. Chen, Julia Davydova, Ryan Shanley, Jane Yuet Ching Hui, Anne Blaes, Helen M. Parsons and Ronda S. Farah. Their work appears in journals such as Biomedicines, Molecular Therapy — Oncolytics, Breast Cancer Research and Treatment, Viruses and Annals of Surgical Oncology.

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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