Gian Marco De Donatis

32 total papers · 1.4k total citations
19 papers, 780 citations indexed

About

Gian Marco De Donatis is a scholar working on Molecular Biology, Genetics and Oncology. According to data from OpenAlex, Gian Marco De Donatis has authored 19 papers receiving a total of 780 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 4 papers in Genetics and 4 papers in Oncology. Recurrent topics in Gian Marco De Donatis's work include melanin and skin pigmentation (4 papers), Coagulation, Bradykinin, Polyphosphates, and Angioedema (4 papers) and RNA and protein synthesis mechanisms (3 papers). Gian Marco De Donatis is often cited by papers focused on melanin and skin pigmentation (4 papers), Coagulation, Bradykinin, Polyphosphates, and Angioedema (4 papers) and RNA and protein synthesis mechanisms (3 papers). Gian Marco De Donatis collaborates with scholars based in United States, France and Canada. Gian Marco De Donatis's co-authors include Thierry Passeron, Bérengère Chignon‐Sicard, Claire Regazzetti, Stéphane Rocchi, Chad Schwartz, Peixuan Guo, Delphine Debayle, Françoise Bernerd, Michael R. Maurizi and Laura Sormani and has published in prestigious journals such as Journal of Biological Chemistry, The EMBO Journal and Biochemistry.

In The Last Decade

Gian Marco De Donatis

18 papers receiving 759 citations

Author Peers

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

Author						Papers	Cites
Gian Marco De Donatis	407	222	192	99	88	19	780
Bruce K. Wetzel	352 0.9×	73 0.3×	234 1.2×	45 0.5×	60 0.7×	18	886
Michelle Byrom	565 1.4×	104 0.5×	38 0.2×	53 0.5×	71 0.8×	21	786
Peh Fern Ong	556 1.4×	86 0.4×	160 0.8×	28 0.3×	47 0.5×	14	810
Mauro Mezzina	652 1.6×	107 0.5×	164 0.9×	91 0.9×	13 0.1×	26	903
Stefania Francesconi	556 1.4×	72 0.3×	134 0.7×	57 0.6×	15 0.2×	26	695
Steven E. Freeman	405 1.0×	368 1.7×	85 0.4×	83 0.8×	19 0.2×	18	780
Kelly Theriault	504 1.2×	28 0.1×	40 0.2×	105 1.1×	65 0.7×	12	829
Hironori Matsuura	250 0.6×	65 0.3×	114 0.6×	97 1.0×	13 0.1×	24	692
David Enshell‐Seijffers	386 0.9×	203 0.9×	294 1.5×	28 0.3×	54 0.6×	13	871
Gayle A. Shinder	383 0.9×	65 0.3×	86 0.4×	26 0.3×	95 1.1×	14	712

Countries citing papers authored by Gian Marco De Donatis

Since Specialization

Citations

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

Fields of papers citing papers by Gian Marco De Donatis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gian Marco De Donatis. 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 Gian Marco De Donatis. The network helps show where Gian Marco De Donatis may publish in the future.

Co-authorship network of co-authors of Gian Marco De Donatis

This figure shows the co-authorship network connecting the top 25 collaborators of Gian Marco De Donatis. A scholar is included among the top collaborators of Gian Marco De Donatis 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 Gian Marco De Donatis. Gian Marco De Donatis 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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