Thiago Guzella

920 total citations · 1 hit paper
9 papers, 546 citations indexed

About

Thiago Guzella is a scholar working on Genetics, Ecology and Epidemiology. According to data from OpenAlex, Thiago Guzella has authored 9 papers receiving a total of 546 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Genetics, 3 papers in Ecology and 2 papers in Epidemiology. Recurrent topics in Thiago Guzella's work include Evolution and Genetic Dynamics (3 papers), Physiological and biochemical adaptations (2 papers) and Influenza Virus Research Studies (1 paper). Thiago Guzella is often cited by papers focused on Evolution and Genetic Dynamics (3 papers), Physiological and biochemical adaptations (2 papers) and Influenza Virus Research Studies (1 paper). Thiago Guzella collaborates with scholars based in Portugal, France and United States. Thiago Guzella's co-authors include Walmir M. Caminhas, Henrique Teotónio, Wentao Yang, Hinrich Schulenburg, Philip Rosenstiel, Barbara Pees, Andrei Papkou, Ivo M. Chelo, Ania Pino-Querido and Luke M. Noble and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Genetics.

In The Last Decade

Thiago Guzella

9 papers receiving 499 citations

Hit Papers

A review of machine learning approaches to Spam filtering 2009 2026 2014 2020 2009 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Thiago Guzella Portugal 5 270 239 157 94 54 9 546
Heather J. Goldsby United States 13 277 1.0× 177 0.7× 117 0.7× 160 1.7× 52 1.0× 31 523
Steven Myers United States 13 157 0.6× 169 0.7× 158 1.0× 99 1.1× 48 0.9× 43 615
William H. Hsu United States 14 326 1.2× 203 0.8× 79 0.5× 33 0.4× 93 1.7× 48 647
Mei‐Hui Wang Taiwan 15 89 0.3× 49 0.2× 67 0.4× 256 2.7× 169 3.1× 39 1.0k
Arnab Bhattacharya India 14 230 0.9× 157 0.7× 114 0.7× 50 0.5× 160 3.0× 67 768
Loretta Auvil United States 16 167 0.6× 68 0.3× 59 0.4× 225 2.4× 387 7.2× 38 832
Fernando Esponda United States 11 275 1.0× 39 0.2× 136 0.9× 46 0.5× 53 1.0× 15 498
Juan Manuel Rodríguez Argentina 15 181 0.7× 273 1.1× 208 1.3× 60 0.6× 18 0.3× 65 713
David B. Knoester United States 14 184 0.7× 76 0.3× 115 0.7× 225 2.4× 174 3.2× 29 662
Thomas J. Marlowe United States 16 231 0.9× 153 0.6× 223 1.4× 119 1.3× 12 0.2× 107 851

Countries citing papers authored by Thiago Guzella

Since Specialization
Citations

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

Fields of papers citing papers by Thiago Guzella

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thiago Guzella

This figure shows the co-authorship network connecting the top 25 collaborators of Thiago Guzella. A scholar is included among the top collaborators of Thiago Guzella 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 Thiago Guzella. Thiago Guzella is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Mallard, François, et al.. (2023). Phenotypic stasis with genetic divergence. SHILAP Revista de lepidopterología. 3. 4 indexed citations
2.
Guzella, Thiago, Vasco M. Barreto, & Jorge Carneiro. (2020). Partitioning stable and unstable expression level variation in cell populations: A theoretical framework and its application to the T cell receptor. PLoS Computational Biology. 16(8). e1007910–e1007910. 2 indexed citations
3.
Papkou, Andrei, Thiago Guzella, Wentao Yang, et al.. (2018). The genomic basis of Red Queen dynamics during rapid reciprocal host–pathogen coevolution. Proceedings of the National Academy of Sciences. 116(3). 923–928. 86 indexed citations
4.
Guzella, Thiago, et al.. (2018). Data from: Slower environmental change hinders adaptation from standing genetic variation. Data Archiving and Networked Services (DANS). 1 indexed citations
5.
Guzella, Thiago, et al.. (2018). Slower environmental change hinders adaptation from standing genetic variation. PLoS Genetics. 14(11). e1007731–e1007731. 18 indexed citations
6.
Guzella, Thiago, et al.. (2018). Towards Interactive Feature Selection with Human-in-the-loop.. 85–88. 1 indexed citations
7.
Noble, Luke M., Ivo M. Chelo, Thiago Guzella, et al.. (2017). Polygenicity and Epistasis Underlie Fitness-Proximal Traits in the Caenorhabditis elegans Multiparental Experimental Evolution (CeMEE) Panel. Genetics. 207(4). 1663–1685. 49 indexed citations
8.
Guzella, Thiago & Walmir M. Caminhas. (2009). A review of machine learning approaches to Spam filtering. Expert Systems with Applications. 36(7). 10206–10222. 369 indexed citations breakdown →
9.
Guzella, Thiago, et al.. (2008). Identification of SPAM messages using an approach inspired on the immune system. Biosystems. 92(3). 215–225. 16 indexed citations

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026