Daniela Raciti

9 papers and 240 indexed citations i.

About

Daniela Raciti is a scholar working on Molecular Biology, Genetics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Daniela Raciti has authored 9 papers receiving a total of 240 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 4 papers in Genetics and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Daniela Raciti’s work include Biomedical Text Mining and Ontologies (4 papers), Genetic and Kidney Cyst Diseases (3 papers) and Image Retrieval and Classification Techniques (2 papers). Daniela Raciti is often cited by papers focused on Biomedical Text Mining and Ontologies (4 papers), Genetic and Kidney Cyst Diseases (3 papers) and Image Retrieval and Classification Techniques (2 papers). Daniela Raciti collaborates with scholars based in United States, Switzerland and Canada. Daniela Raciti's co-authors include André W. Brändli, Luca Reggiani Bonetti, Rannar Airik, Andreas Kispert, Duncan Davidson, Astrid Subrizi, Dave Clements, Christopher Tindal, Brigitte Kaissling and Lars Geffers and has published in prestigious journals such as Genes & Development, Bioinformatics and Genome biology.

In The Last Decade

Co-authorship network of co-authors of Daniela Raciti i

Fields of papers citing papers by Daniela Raciti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Daniela Raciti

Since Specialization
Citations

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