Marcelo Ganzella

63 total papers · 1.3k total citations
35 papers, 890 citations indexed

About

Marcelo Ganzella is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Cell Biology. According to data from OpenAlex, Marcelo Ganzella has authored 35 papers receiving a total of 890 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 20 papers in Cellular and Molecular Neuroscience and 11 papers in Cell Biology. Recurrent topics in Marcelo Ganzella's work include Neuroscience and Neuropharmacology Research (20 papers), Lipid Membrane Structure and Behavior (12 papers) and Cellular transport and secretion (11 papers). Marcelo Ganzella is often cited by papers focused on Neuroscience and Neuropharmacology Research (20 papers), Lipid Membrane Structure and Behavior (12 papers) and Cellular transport and secretion (11 papers). Marcelo Ganzella collaborates with scholars based in Germany, Brazil and United States. Marcelo Ganzella's co-authors include Diogo O. Souza, Reinhard Jahn, Roberto Farina Almeida, Carina Rodrigues Boeck, Deusa Vendite, Xiandeng Wu, Mingjie Zhang, Julia Preobraschenski, Samanta Oliveira Loureiro and Gisele Hansel and has published in prestigious journals such as Nature, Cell and Nature Communications.

In The Last Decade

Marcelo Ganzella

35 papers receiving 881 citations

Author Peers

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

Author Last Decade Papers Cites
Marcelo Ganzella 437 310 161 133 115 35 890
João Pedro Lopes 374 0.9× 272 0.9× 86 0.5× 184 1.4× 350 3.0× 32 971
Carol L. Zielke 573 1.3× 275 0.9× 99 0.6× 39 0.3× 149 1.3× 26 1.0k
Anti Kalda 556 1.3× 362 1.2× 41 0.3× 123 0.9× 91 0.8× 33 1.0k
Dekun Song 315 0.7× 202 0.7× 53 0.3× 92 0.7× 126 1.1× 30 952
Paola Tarroni 573 1.3× 322 1.0× 41 0.3× 61 0.5× 106 0.9× 22 930
Magdalena Cieślik 256 0.6× 93 0.3× 54 0.3× 93 0.7× 187 1.6× 32 733
Dominique Demeyer 283 0.6× 236 0.8× 53 0.3× 53 0.4× 369 3.2× 23 818
Gang Zhu 328 0.8× 309 1.0× 101 0.6× 38 0.3× 69 0.6× 35 751
Regina Célia Cussa Kubrusly 339 0.8× 397 1.3× 40 0.2× 68 0.5× 67 0.6× 36 700
Olga Nikodijević 351 0.8× 344 1.1× 59 0.4× 500 3.8× 127 1.1× 20 961

Countries citing papers authored by Marcelo Ganzella

Since Specialization
Citations

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

Fields of papers citing papers by Marcelo Ganzella

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marcelo Ganzella. 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 Marcelo Ganzella. The network helps show where Marcelo Ganzella may publish in the future.

Co-authorship network of co-authors of Marcelo Ganzella

This figure shows the co-authorship network connecting the top 25 collaborators of Marcelo Ganzella. A scholar is included among the top collaborators of Marcelo Ganzella 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 Marcelo Ganzella. Marcelo Ganzella 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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