Philip Snell

1.7k citations
11 papers · 939 · h-index 9

Impact in

    • Pluripotent Stem Cells Research
    • CRISPR and Genetic Engineering
    • Renal and related cancers
    • Single-cell and spatial transcriptomics
    • Metabolomics and Mass Spectrometry Studies
    • Epigenetics and DNA Methylation

Papers in

    • Pluripotent Stem Cells Research 5
    • Renal and related cancers 4
    • Genomics and Chromatin Dynamics 2
    • Metabolomics and Mass Spectrometry Studies 2
    • Microbial Metabolic Engineering and Bioproduction 2

Philip Snell

11 papers receiving 928 citations

Peers

Philip Snell
Comparison fields: 5 of 75
  • Molecular Biology 740
  • Obstetrics and Gynecology 35
  • Genetics 127
  • Public Health, Environmental and Occupational Health 121
  • Immunology 86
Replace Natalie K. Ryan with:
Natalie K. Ryan Australia
Keiji Hirabayashi Japan
Hiroko Hata Japan
Mélanie Eckersley-Maslin United Kingdom
David L’Hôte France
Weishi Yu China
Celia Alda-Catalinas United Kingdom
Yoichi Sekita Japan
R.L. Gardner United Kingdom
Hitomi Yatsuki Japan
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Citations per field
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Citations per year

Countries citing papers authored by Philip Snell

Since Specialization
Citations

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

Fields of papers citing papers by Philip Snell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

11 of 11 papers shown
#Work
1 2015345
2 2011186
3 200494
4 202181
5 200369
6 200155
7 200552
8 200430
9 200321
10 20173
11 20203

About Philip Snell

Philip Snell is a scholar working on Molecular Biology, Surgery, Aquatic Science, Public Health, Environmental and Occupational Health and Hematology, having authored 11 papers that have together received 939 indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (5 papers), Renal and related cancers (4 papers), Genomics and Chromatin Dynamics (2 papers), Metabolomics and Mass Spectrometry Studies (2 papers), Microbial Metabolic Engineering and Bioproduction (2 papers), Fish Biology and Ecology Studies (1 paper), T-cell and B-cell Immunology (1 paper) and Chromosomal and Genetic Variations (1 paper). The work is most often cited by research in Molecular Biology (740 citations), Obstetrics and Gynecology (35 citations), Genetics (127 citations), Public Health, Environmental and Occupational Health (121 citations) and Immunology (86 citations). Philip Snell has collaborated with scholars based in United Kingdom, United States and Netherlands. Frequent co-authors include Kay Elder, Leila Christie, Greg Elgar, Xiaoming Hu, Paul Blakeley, Ignacio del Valle, Paul Robson, Norah M. E. Fogarty, Sissy E. Wamaitha and Kathy K. Niakan. Their work appears in journals such as OMICS A Journal of Integrative Biology, Nature Communications, Thrombosis and Haemostasis, Genomics and Mammalian Genome.

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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