Philip Gribbon

3.6k citations
83 papers · 1.5k indexed · h-index 22
Topics
Computational Drug Discovery Methods (18 papers)SARS-CoV-2 and COVID-19 Research (10 papers)Receptor Mechanisms and Signaling (7 papers)
Journals
Journal of Biological ChemistrySHILAP Revista de lepidopterologíaBioinformatics

In The Last Decade

Philip Gribbon

78 papers receiving 1.4k citations

Peers

Philip Gribbon
Comparison fields: 5 of 142
  • Molecular Biology 739
  • Computational Theory and Mathematics 240
  • Organic Chemistry 194
  • Cell Biology 181
  • Biomedical Engineering 146
Replace Rita Grandori with:
Rita Grandori Italy
G. Sitta Sittampalam United States
Jeanne A. Hardy United States
Andrea Bernini Italy
Hui Sun Lee United States
Hongxiang Hu United States
Xubo Lin China
Ping Cao United States
Antonio Pineda‐Lucena Spain
Margaret Lee United States
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Citations per field
00.5×1.5×
Rita Grandori · 1×
Citations per year

Countries citing papers authored by Philip Gribbon

Since Specialization
Citations

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

Fields of papers citing papers by Philip Gribbon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Philip Gribbon

This figure shows the co-authorship network connecting the top 25 collaborators of Philip Gribbon. A scholar is included among the top collaborators of Philip Gribbon based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Philip Gribbon. Philip Gribbon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 1
4 8
5 1
6 7
7 6
8 2
9 5
10 5
11 8
12 35
13 52
14 7
15 10
16 8
17 27
18 6
19 2
20 15

About Philip Gribbon

Philip Gribbon is a scholar working on Biophysics, Health Informatics and Computational Theory and Mathematics, having authored 83 papers that have together received 1.5k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (18 papers), SARS-CoV-2 and COVID-19 Research (10 papers) and Receptor Mechanisms and Signaling (7 papers). The work is most often cited by research in Computational Theory and Mathematics (240 citations), Biophysics (87 citations) and Cell Biology (181 citations). Philip Gribbon has collaborated with scholars based in Germany, United Kingdom and Italy. Frequent co-authors include Tim Hardingham, Boon Chin Heng, Andreas Sewing, Sheraz Gul, Andrea Zaliani, Jeanette Reinshagen, Bernhard Ellinger, Malcolm N. Jones, David F. Moore and C. Peter Winlove. Their work appears in journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and Bioinformatics.

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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