Philip Gribbon

3.6k total citations
83 papers, 1.5k citations indexed

About

Philip Gribbon is a scholar working on Molecular Biology, Computational Theory and Mathematics and Infectious Diseases. According to data from OpenAlex, Philip Gribbon has authored 83 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Molecular Biology, 18 papers in Computational Theory and Mathematics and 12 papers in Infectious Diseases. Recurrent topics in Philip Gribbon's work include Computational Drug Discovery Methods (18 papers), SARS-CoV-2 and COVID-19 Research (10 papers) and Receptor Mechanisms and Signaling (7 papers). Philip Gribbon is often cited by papers focused on Computational Drug Discovery Methods (18 papers), SARS-CoV-2 and COVID-19 Research (10 papers) and Receptor Mechanisms and Signaling (7 papers). Philip Gribbon collaborates with scholars based in Germany, United Kingdom and Italy. Philip Gribbon's co-authors include Tim Hardingham, Boon Chin Heng, Andreas Sewing, Andrea Zaliani, Sheraz Gul, Jeanette Reinshagen, Bernhard Ellinger, Khalid Ahmed, Cheng‐Yu Tsai and David F. Moore and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Philip Gribbon

78 papers receiving 1.4k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Philip Gribbon Germany 22 739 240 194 181 146 83 1.5k
Hui Sun Lee United States 22 1.6k 2.2× 322 1.3× 310 1.6× 164 0.9× 98 0.7× 43 2.3k
Heidi Wunderli‐Allenspach Switzerland 33 1.4k 1.9× 144 0.6× 194 1.0× 120 0.7× 216 1.5× 62 2.8k
William J. Allen United Kingdom 22 1.6k 2.2× 458 1.9× 198 1.0× 86 0.5× 117 0.8× 50 2.3k
Rodrigo V. Honorato Brazil 18 1.0k 1.4× 196 0.8× 106 0.5× 99 0.5× 135 0.9× 36 1.6k
Nathan P. Coussens United States 18 969 1.3× 110 0.5× 112 0.6× 75 0.4× 100 0.7× 47 1.8k
Gus R. Rosania United States 22 784 1.1× 131 0.5× 120 0.6× 69 0.4× 225 1.5× 68 1.9k
Jeanne A. Hardy United States 25 1.4k 1.9× 149 0.6× 133 0.7× 193 1.1× 212 1.5× 57 2.1k
Srinivasan Ramachandran United States 32 1.6k 2.1× 199 0.8× 86 0.4× 127 0.7× 281 1.9× 69 2.8k
Dong Lu China 26 1.8k 2.4× 204 0.8× 235 1.2× 80 0.4× 180 1.2× 100 3.0k
Jacquin C. Niles United States 27 1.5k 2.0× 107 0.4× 196 1.0× 154 0.9× 226 1.5× 51 3.1k

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
1.
Gadiya, Yojana, Olga Genilloud, Ursula Bilitewski, et al.. (2025). Predicting Antimicrobial Class Specificity of Small Molecules Using Machine Learning. Journal of Chemical Information and Modeling. 65(5). 2416–2431. 1 indexed citations
2.
Bechtel, Marco, Sandra Ciesek, Philip Gribbon, et al.. (2025). Papaverine Targets STAT Signaling: A Dual‐Action Therapy Option Against SARS‐CoV‐2. Journal of Medical Virology. 97(4). e70319–e70319.
3.
Gadiya, Yojana, et al.. (2024). Exploring SureChEMBL from a drug discovery perspective. Scientific Data. 11(1). 507–507. 6 indexed citations
4.
Balaur, Irina, Hanna Ćwiek‐Kupczyńska, Yojana Gadiya, et al.. (2024). Getting ready for the European Health Data Space (EHDS): IDERHA's plan to align with the latest EHDS requirements for the secondary use of health data. SHILAP Revista de lepidopterología. 4. 160–160. 8 indexed citations
5.
Gribbon, Philip, et al.. (2024). Current state of data stewardship tools in life science. Frontiers in Big Data. 7. 1428568–1428568. 1 indexed citations
6.
Zaliani, Andrea, Undine Haferkamp, Anne Willing, et al.. (2024). Identification and development of TRPM4 antagonists to counteract neuronal excitotoxicity. iScience. 27(12). 111425–111425. 1 indexed citations
7.
Sreeramulu, Sridhar, Christian Richter, Edgar Specker, et al.. (2024). Design, quality and validation of the EU-OPENSCREEN fragment library poised to a high-throughput screening collection. RSC Medicinal Chemistry. 15(4). 1176–1188. 7 indexed citations
8.
Schroeter, Christina B., Christopher Nelke, Marcus Schewe, et al.. (2023). Validation of TREK1 ion channel activators as an immunomodulatory and neuroprotective strategy in neuroinflammation. Biological Chemistry. 404(4). 355–375. 6 indexed citations
9.
Karki, Reagon, Yojana Gadiya, Andrea Zaliani, & Philip Gribbon. (2023). Mpox Knowledge Graph: a comprehensive representation embedding chemical entities and associated biology of Mpox. Bioinformatics Advances. 3(1). vbad045–vbad045. 2 indexed citations
10.
Gadiya, Yojana, Andrea Zaliani, Philip Gribbon, & Martin Hofmann‐Apitius. (2022). PEMT: a patent enrichment tool for drug discovery. Bioinformatics. 39(1). 5 indexed citations
11.
Tanoli, Ziaurrehman, Jehad Aldahdooh, Yinyin Wang, et al.. (2021). Minimal information for chemosensitivity assays (MICHA): a next-generation pipeline to enable the FAIRification of drug screening experiments. Briefings in Bioinformatics. 23(1). 8 indexed citations
12.
Katsen‐Globa, Alisa, André Schulz, Frank Stracke, et al.. (2021). Droplet-based vitrification of adherent human induced pluripotent stem cells on alginate microcarrier influenced by adhesion time and matrix elasticity. Cryobiology. 103. 57–69. 7 indexed citations
13.
Albani, Simone, Maria Kuzikov, Elisa Costanzi, et al.. (2021). A Blueprint for High Affinity SARS-CoV-2 Mpro Inhibitors from Activity-Based Compound Library Screening Guided by Analysis of Protein Dynamics. ACS Pharmacology & Translational Science. 4(3). 1079–1095. 35 indexed citations
14.
Smith, David, Alan G. Buddie, Rebecca J. M. Goss, et al.. (2019). Discovery pipelines for marine resources: an ocean of opportunity for biotechnology?. World Journal of Microbiology and Biotechnology. 35(7). 107–107. 8 indexed citations
15.
Keminer, Oliver, et al.. (2017). A high-content small molecule screen identifies novel inducers of definitive endoderm. Molecular Metabolism. 6(7). 640–650. 27 indexed citations
16.
Ellinger, Bernhard, Anjali Prashar, Johannes Landskron, et al.. (2014). A Phenotypic Screening Approach to Identify Anticancer Compounds Derived from Marine Fungi. Assay and Drug Development Technologies. 12(3). 162–175. 6 indexed citations
17.
18.
Gribbon, Philip, et al.. (2006). A Novel Method for Analyzing [Ca2+] Flux Kinetics in High-Throughput Screening. SLAS DISCOVERY. 11(5). 511–518. 5 indexed citations
19.
Moger, Julian, Philip Gribbon, Andreas Sewing, & C. Peter Winlove. (2006). The Application of Fluorescence Lifetime Readouts in High-Throughput Screening. SLAS DISCOVERY. 11(7). 765–772. 15 indexed citations
20.
Gribbon, Philip, Boon Chin Heng, & Tim Hardingham. (2003). Novel Confocal-FRAP Analysis of Carbohydrate-Protein Interactions Within the Extracellular Matrix. Humana Press eBooks. 171. 487–494. 1 indexed citations

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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