Jay Daniels

643 citations
5 papers · 241 · 1 hit paper · h-index 3

Impact in

Papers in

    • CAR-T cell therapy research 3
    • HER2/EGFR in Cancer Research 1
    • Viral Infectious Diseases and Gene Expression in Insects 2
    • CRISPR and Genetic Engineering 1

Jay Daniels

4 papers receiving 241 citations

Jay Daniels's Hit Papers

Naturally occurring T cell mutations enhance engineered T cell therapies 2024 · 46 citations
460+1Years since publication10203040

Peers

Jay Daniels
Comparison fields: 5 of 52
  • Dermatology 77
  • Aging 9
  • Cellular and Molecular Neuroscience 68
  • Pathology and Forensic Medicine 67
  • Endocrine and Autonomic Systems 23
Replace Almudena Fernández with:
Almudena Fernández Spain
Lakshmi Paniker United States
Wakako Watanabe Japan
Wei‐Meng Woo United States
Yoshiko Ishida Japan
Emil Aamar Israel
Erez Cohen United States
Davide Andrenacci Italy
Yana G. Kamberov United States
Fabien Murisier Switzerland
Jay Daniels relative to Almudena Fernández Spain Almudena Fernández's profile →
Citations per field
00.5×11.2×
Almudena Fernández · 1×
Citations per year

Countries citing papers authored by Jay Daniels

Since Specialization
Citations

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

Fields of papers citing papers by Jay Daniels

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

5 of 5 papers shown
#Work
1 2017112
2 201781
3
Naturally occurring T cell mutations enhance engineered T cell therapies
Hit paper breakdown →
202446
4 20222
5 20230

About Jay Daniels

Jay Daniels is a scholar working on Oncology, Molecular Biology, Genetics, Pathology and Forensic Medicine and Cellular and Molecular Neuroscience, having authored 5 papers that have together received 241 indexed citations. Recurring topics across this work include CAR-T cell therapy research (3 papers), Viral Infectious Diseases and Gene Expression in Insects (2 papers), Lymphoma Diagnosis and Treatment (1 paper), HER2/EGFR in Cancer Research (1 paper), Insect Utilization and Effects (1 paper), CRISPR and Genetic Engineering (1 paper), Cutaneous lymphoproliferative disorders research (1 paper) and Circadian rhythm and melatonin (1 paper). The work is most often cited by research in Dermatology (77 citations), Aging (9 citations), Cellular and Molecular Neuroscience (68 citations), Pathology and Forensic Medicine (67 citations) and Endocrine and Autonomic Systems (23 citations). Jay Daniels has collaborated with scholars based in United States. Frequent co-authors include Jaehyuk Choi, Sha Liu, Mark N. Wu, Lay Kodama, Qili Liu, Masashi Tabuchi, Joonhee Park, Akshaya Ramachandran, Barbara Pro and Joan Guitart. Their work appears in journals such as Blood, Nature, Science and Journal of Investigative Dermatology.

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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