Simone C. da Silva Rosa

41 total papers · 991 total citations
20 papers, 639 citations indexed

About

Simone C. da Silva Rosa is a scholar working on Molecular Biology, Epidemiology and Cancer Research. According to data from OpenAlex, Simone C. da Silva Rosa has authored 20 papers receiving a total of 639 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 11 papers in Epidemiology and 5 papers in Cancer Research. Recurrent topics in Simone C. da Silva Rosa's work include Autophagy in Disease and Therapy (8 papers), Lipid metabolism and biosynthesis (3 papers) and Adipose Tissue and Metabolism (3 papers). Simone C. da Silva Rosa is often cited by papers focused on Autophagy in Disease and Therapy (8 papers), Lipid metabolism and biosynthesis (3 papers) and Adipose Tissue and Metabolism (3 papers). Simone C. da Silva Rosa collaborates with scholars based in Canada, Iran and United States. Simone C. da Silva Rosa's co-authors include Joseph W. Gordon, Saeid Ghavami, Meilian Liu, Gary Sweeney, Javad Alizadeh, Shahla Shojaei, James A. Thliveris, Stevan Pecic, Amir A. Zeki and Marek Łoś and has published in prestigious journals such as International Journal of Molecular Sciences, European Journal of Pharmacology and Autophagy.

In The Last Decade

Simone C. da Silva Rosa

19 papers receiving 635 citations

Author Peers

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

Author Last Decade Papers Cites
Simone C. da Silva Rosa 276 239 136 135 87 20 639
Motoko Kanzaki 235 0.9× 196 0.8× 158 1.2× 138 1.0× 129 1.5× 17 684
Xiong Jia 257 0.9× 127 0.5× 82 0.6× 83 0.6× 68 0.8× 26 562
Jin Woo Choi 377 1.4× 149 0.6× 71 0.5× 178 1.3× 69 0.8× 23 741
Kyu-Sil Choi 382 1.4× 149 0.6× 104 0.8× 95 0.7× 58 0.7× 13 781
Pengcheng Luo 374 1.4× 204 0.9× 181 1.3× 67 0.5× 84 1.0× 26 768
Agata Wrońska 188 0.7× 160 0.7× 69 0.5× 295 2.2× 81 0.9× 24 654
Emma L. Shepherd 154 0.6× 219 0.9× 57 0.4× 97 0.7× 94 1.1× 24 625
Xiao Liu 218 0.8× 287 1.2× 53 0.4× 84 0.6× 123 1.4× 25 726
Yun Zhang 274 1.0× 171 0.7× 102 0.8× 161 1.2× 119 1.4× 25 790
Isabelle K. Vila 369 1.3× 154 0.6× 84 0.6× 194 1.4× 59 0.7× 20 705

Countries citing papers authored by Simone C. da Silva Rosa

Since Specialization
Citations

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

Fields of papers citing papers by Simone C. da Silva Rosa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Simone C. da Silva 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 Simone C. da Silva Rosa. The network helps show where Simone C. da Silva Rosa may publish in the future.

Co-authorship network of co-authors of Simone C. da Silva Rosa

This figure shows the co-authorship network connecting the top 25 collaborators of Simone C. da Silva Rosa. A scholar is included among the top collaborators of Simone C. da Silva 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 Simone C. da Silva Rosa. Simone C. da Silva 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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