Maya Sangesland

23 papers and 977 indexed citations i.

About

Maya Sangesland is a scholar working on Molecular Biology, Immunology and Epidemiology. According to data from OpenAlex, Maya Sangesland has authored 23 papers receiving a total of 977 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 9 papers in Immunology and 8 papers in Epidemiology. Recurrent topics in Maya Sangesland’s work include Influenza Virus Research Studies (7 papers), Monoclonal and Polyclonal Antibodies Research (6 papers) and SARS-CoV-2 and COVID-19 Research (6 papers). Maya Sangesland is often cited by papers focused on Influenza Virus Research Studies (7 papers), Monoclonal and Polyclonal Antibodies Research (6 papers) and SARS-CoV-2 and COVID-19 Research (6 papers). Maya Sangesland collaborates with scholars based in United States, Germany and Canada. Maya Sangesland's co-authors include Matt Kaeberlein, Simon C. Johnson, Peter S. Rabinovitch, Daniel Lingwood, Jessica Hui, Anthony S. Castanza, Brian M. Wasko, Ernst‐Bernhard Kayser, Fresnida J. Ramos and Margaret M. Sedensky and has published in prestigious journals such as Science, Nature Communications and Immunity.

In The Last Decade

Co-authorship network of co-authors of Maya Sangesland i

Fields of papers citing papers by Maya Sangesland

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Maya Sangesland

Since Specialization
Citations

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

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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2025