David Fashena

21 total papers · 1.9k total citations
12 papers, 546 citations indexed

About

David Fashena is a scholar working on Molecular Biology, Cell Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, David Fashena has authored 12 papers receiving a total of 546 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 2 papers in Cell Biology and 1 paper in Cellular and Molecular Neuroscience. Recurrent topics in David Fashena's work include Biomedical Text Mining and Ontologies (8 papers), Bioinformatics and Genomic Networks (6 papers) and Genetics, Bioinformatics, and Biomedical Research (5 papers). David Fashena is often cited by papers focused on Biomedical Text Mining and Ontologies (8 papers), Bioinformatics and Genomic Networks (6 papers) and Genetics, Bioinformatics, and Biomedical Research (5 papers). David Fashena collaborates with scholars based in United States. David Fashena's co-authors include Monte Westerfield, Yvonne M. Bradford, Leyla Ruzicka, Sridhar Ramachandran, Douglas G. Howe, Ceri E. Van Slyke, Ken Frazer, Holly Paddock, Ryan Martin and Amy Singer and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and The Journal of Comparative Neurology.

In The Last Decade

David Fashena

11 papers receiving 540 citations

Hit Papers

Zebrafish information net... 2022 2026 2023 2024 2022 25 50 75 100

Author Peers

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

Author Last Decade Papers Cites
David Fashena 341 172 78 66 55 12 546
Josette M. Ungos 394 1.2× 172 1.0× 64 0.8× 55 0.8× 41 0.7× 6 513
Andrés F. Sarrazin 306 0.9× 100 0.6× 52 0.7× 109 1.7× 97 1.8× 13 499
Agnès Degrave 409 1.2× 167 1.0× 94 1.2× 19 0.3× 53 1.0× 7 603
Gianfranco Bellipanni 406 1.2× 179 1.0× 71 0.9× 25 0.4× 19 0.3× 26 587
Sabrina Toro 353 1.0× 183 1.1× 88 1.1× 12 0.2× 36 0.7× 16 576
Kyeong‐Won Yoo 391 1.1× 255 1.5× 86 1.1× 20 0.3× 18 0.3× 17 593
Arish N Shah 387 1.1× 201 1.2× 94 1.2× 18 0.3× 16 0.3× 12 577
Guillaume Pézeron 252 0.7× 225 1.3× 33 0.4× 23 0.3× 18 0.3× 20 600
Lydia Djenoune 229 0.7× 243 1.4× 127 1.6× 41 0.6× 26 0.5× 15 603
Chathurani S. Jayasena 348 1.0× 69 0.4× 50 0.6× 220 3.3× 57 1.0× 9 531

Countries citing papers authored by David Fashena

Since Specialization
Citations

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

Fields of papers citing papers by David Fashena

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Fashena

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