Marcelo Cicconet

62 total papers · 2.7k total citations
29 papers, 1.3k citations indexed

About

Marcelo Cicconet is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology and Biophysics. According to data from OpenAlex, Marcelo Cicconet has authored 29 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 10 papers in Molecular Biology and 6 papers in Biophysics. Recurrent topics in Marcelo Cicconet's work include Cell Image Analysis Techniques (6 papers), Single-cell and spatial transcriptomics (5 papers) and Music Technology and Sound Studies (4 papers). Marcelo Cicconet is often cited by papers focused on Cell Image Analysis Techniques (6 papers), Single-cell and spatial transcriptomics (5 papers) and Music Technology and Sound Studies (4 papers). Marcelo Cicconet collaborates with scholars based in United States, Brazil and Germany. Marcelo Cicconet's co-authors include Bernardo L. Sabatini, Siniša Hrvatin, Michael E. Greenberg, Daniel R. Hochbaum, Lucas Cheadle, Rebeca Borges-Monroy, Allon M. Klein, Rapolas Žilionis, Keiramarie Robertson and M. Aurel Nagy and has published in prestigious journals such as Nature, Nature Communications and The Journal of Cell Biology.

In The Last Decade

Marcelo Cicconet

27 papers receiving 1.3k citations

Hit Papers

Immuno-SABER enables high... 2019 2026 2021 2023 2019 100 200 300

Author Peers

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

Author Last Decade Papers Cites
Marcelo Cicconet 754 240 169 127 116 29 1.3k
Paul C. Goodwin 800 1.1× 290 1.2× 144 0.9× 129 1.0× 118 1.0× 27 1.8k
Talley J. Lambert 730 1.0× 299 1.2× 166 1.0× 116 0.9× 102 0.9× 23 1.5k
Sam Vesuna 942 1.2× 327 1.4× 269 1.6× 256 2.0× 87 0.8× 14 1.5k
Christoph Kirst 584 0.8× 312 1.3× 250 1.5× 325 2.6× 117 1.0× 23 1.5k
Wei Zhou 470 0.6× 456 1.9× 73 0.4× 118 0.9× 168 1.4× 58 1.4k
Megumi Eguchi 551 0.7× 320 1.3× 476 2.8× 207 1.6× 99 0.9× 18 1.6k
Bo Shui 693 0.9× 316 1.3× 116 0.7× 47 0.4× 163 1.4× 35 1.3k
Kana Namiki 625 0.8× 195 0.8× 250 1.5× 120 0.9× 64 0.6× 20 1.2k
Toru Matsuura 1.2k 1.5× 378 1.6× 118 0.7× 63 0.5× 52 0.4× 48 1.8k
Mohan Bolisetty 1.2k 1.6× 193 0.8× 73 0.4× 129 1.0× 71 0.6× 18 1.8k

Countries citing papers authored by Marcelo Cicconet

Since Specialization
Citations

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

Fields of papers citing papers by Marcelo Cicconet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marcelo Cicconet

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