Maria De Rosa

56 total papers · 972 total citations
38 papers, 713 citations indexed

About

Maria De Rosa is a scholar working on Molecular Biology, Organic Chemistry and Infectious Diseases. According to data from OpenAlex, Maria De Rosa has authored 38 papers receiving a total of 713 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 9 papers in Organic Chemistry and 6 papers in Infectious Diseases. Recurrent topics in Maria De Rosa's work include Pharmacological Effects and Toxicity Studies (4 papers), Chemical Synthesis and Analysis (4 papers) and Drug Transport and Resistance Mechanisms (4 papers). Maria De Rosa is often cited by papers focused on Pharmacological Effects and Toxicity Studies (4 papers), Chemical Synthesis and Analysis (4 papers) and Drug Transport and Resistance Mechanisms (4 papers). Maria De Rosa collaborates with scholars based in Italy, Belgium and Sweden. Maria De Rosa's co-authors include Giovanna Li Petri, Hugues Chanteux, Armel Stockis, Federica Durante, Cristina Baldissarri, Roberta Rosa Valtorta, Marcello Gallucci, Alessandro Gabbiadini, Federico Corelli and Serena Pasquini and has published in prestigious journals such as SHILAP Revista de lepidopterología, Neurology and International Journal of Molecular Sciences.

In The Last Decade

Maria De Rosa

37 papers receiving 700 citations

Author Peers

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

Author						Papers	Cites
Maria De Rosa	252	195	109	106	87	38	713
Matthew Gross	216 0.9×	174 0.9×	83 0.8×	57 0.5×	40 0.5×	27	751
Yoshihiro Sugiura	252 1.0×	293 1.5×	68 0.6×	24 0.2×	31 0.4×	44	732
Ian T. Crosby	344 1.4×	216 1.1×	138 1.3×	117 1.1×	28 0.3×	47	878
Yue Dong	244 1.0×	61 0.3×	36 0.3×	73 0.7×	15 0.2×	55	871
Kumaraswamy Naidu Chitrala	339 1.3×	176 0.9×	23 0.2×	96 0.9×	42 0.5×	45	729
Hui-Ju Chen	237 0.9×	70 0.4×	18 0.2×	43 0.4×	41 0.5×	33	670
Sunil Aggarwal	137 0.5×	94 0.5×	59 0.5×	306 2.9×	75 0.9×	59	719
X Rabasseda	254 1.0×	150 0.8×	36 0.3×	127 1.2×	17 0.2×	81	816
Weiwei Liu	197 0.8×	86 0.4×	24 0.2×	40 0.4×	28 0.3×	74	851
Francesca Rossi	139 0.6×	479 2.5×	43 0.4×	202 1.9×	120 1.4×	46	868

Countries citing papers authored by Maria De Rosa

Since Specialization

Citations

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

Fields of papers citing papers by Maria De Rosa

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maria De Rosa

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