Jay Naik

848 citations
11 papers · 193 · h-index 6

Impact in

    • CAR-T cell therapy research
    • Virus-based gene therapy research

Papers in

    • CAR-T cell therapy research 2
    • Cancer Treatment and Pharmacology 2
    • HER2/EGFR in Cancer Research 2
    • Virus-based gene therapy research 2

Jay Naik

11 papers receiving 188 citations

Peers

Jay Naik
Comparison fields: 5 of 38
  • Oncology 107
  • Genetics 99
  • Reproductive Medicine 23
  • Biotechnology 19
  • Immunology 29
Replace Katharine Bailey with:
Katharine Bailey United Kingdom
Daw‐Jen Tsuei Taiwan
Peter Kyriakou Australia
Padma Pandurang Nanaware United States
Qian‐Ying Zhu China
Yoshiko Shirakiya Japan
Annemarie Boerma Netherlands
Elizabeth S. Appleton United Kingdom
Dominic Curran United States
Jay Naik relative to Katharine Bailey United Kingdom Katharine Bailey's profile →
Citations per field
00.5×2×4×5.8×
Katharine Bailey · 1×
Citations per year

Countries citing papers authored by Jay Naik

Since Specialization
Citations

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

Fields of papers citing papers by Jay Naik

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

11 of 11 papers shown
#Work
1 200881
2 201132
3 201125
4 200819
5 201813
6 20128
7
Effects of perioperative lapatinib and trastuzumab, alone and in combination, in early HER2+breast cancer - the UK EPHOS-B trial (CRUK/08/002)
20164
8 20233
9 20063
10 20173
11 20242

About Jay Naik

Jay Naik is a scholar working on Oncology, Genetics, Obstetrics and Gynecology, Reproductive Medicine and Pulmonary and Respiratory Medicine, having authored 11 papers that have together received 193 indexed citations. Recurring topics across this work include CAR-T cell therapy research (2 papers), Virus-based gene therapy research (2 papers), Cancer Treatment and Pharmacology (2 papers), HER2/EGFR in Cancer Research (2 papers), Ovarian cancer diagnosis and treatment (1 paper), Lymphoma Diagnosis and Treatment (1 paper), Viral Infections and Outbreaks Research (1 paper) and Nausea and vomiting management (1 paper). The work is most often cited by research in Oncology (107 citations), Genetics (99 citations), Reproductive Medicine (23 citations), Biotechnology (19 citations) and Immunology (29 citations). Jay Naik has collaborated with scholars based in United Kingdom, United States and Denmark. Frequent co-authors include John David Chester, Richard G. Vile, Peter John Selby, Jenny F. Seligmann, Timothy John Perren, Chris J. Twelves, John Cameron Bell, Alan A. Melcher, Kevin Joseph Harrington and Candice L. Willmon. Their work appears in journals such as BMC Cancer, Lung Cancer, ESMO Open, Clinical Cancer Research and PLoS ONE.

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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