Chris De Savi

77 total papers · 1.6k total citations
28 papers, 517 citations indexed

About

Chris De Savi is a scholar working on Molecular Biology, Organic Chemistry and Oncology. According to data from OpenAlex, Chris De Savi has authored 28 papers receiving a total of 517 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 9 papers in Organic Chemistry and 8 papers in Oncology. Recurrent topics in Chris De Savi's work include Protease and Inhibitor Mechanisms (4 papers), Carbohydrate Chemistry and Synthesis (4 papers) and Peptidase Inhibition and Analysis (3 papers). Chris De Savi is often cited by papers focused on Protease and Inhibitor Mechanisms (4 papers), Carbohydrate Chemistry and Synthesis (4 papers) and Peptidase Inhibition and Analysis (3 papers). Chris De Savi collaborates with scholars based in United Kingdom, United States and South Korea. Chris De Savi's co-authors include Ian Paterson, Matthew T. Tudge, David L. Hughes, Lisbet Kværnø, Martin G. Banwell, Keith G. Watson, G. T. Crisp, Yulin Jiang, Attilla Ting and David C. R. Hockless and has published in prestigious journals such as Journal of Clinical Oncology, The Journal of Immunology and Cancer Research.

In The Last Decade

Chris De Savi

27 papers receiving 497 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Chris De Savi 263 212 130 72 53 28 517
Guoyi Yan 223 0.8× 320 1.5× 123 0.9× 56 0.8× 36 0.7× 36 597
Dana M. Zaher 141 0.5× 247 1.2× 120 0.9× 35 0.5× 42 0.8× 30 577
Anne M. Strimpler 157 0.6× 283 1.3× 156 1.2× 42 0.6× 33 0.6× 18 585
Keiji Kamiyama 328 1.2× 317 1.5× 155 1.2× 49 0.7× 50 0.9× 17 572
Manolis A. Fousteris 341 1.3× 272 1.3× 97 0.7× 21 0.3× 27 0.5× 40 587
Gwan Sun Lee 204 0.8× 309 1.5× 237 1.8× 79 1.1× 36 0.7× 21 594
Andrii Monastyrskyi 181 0.7× 309 1.5× 166 1.3× 85 1.2× 18 0.3× 25 608
Danny Hsu 184 0.7× 213 1.0× 116 0.9× 32 0.4× 40 0.8× 27 502
Antonella Pepe 227 0.9× 264 1.2× 108 0.8× 26 0.4× 52 1.0× 25 548
Shuyuan Zhao 152 0.6× 331 1.6× 212 1.6× 19 0.3× 33 0.6× 20 533

Countries citing papers authored by Chris De Savi

Since Specialization
Citations

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

Fields of papers citing papers by Chris De Savi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chris De Savi. 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 Chris De Savi. The network helps show where Chris De Savi may publish in the future.

Co-authorship network of co-authors of Chris De Savi

This figure shows the co-authorship network connecting the top 25 collaborators of Chris De Savi. A scholar is included among the top collaborators of Chris De Savi 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 Chris De Savi. Chris De Savi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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