Daniel Urda

42 papers and 928 indexed citations i.

About

Daniel Urda is a scholar working on Molecular Biology, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Daniel Urda has authored 42 papers receiving a total of 928 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 9 papers in Artificial Intelligence and 9 papers in Computer Vision and Pattern Recognition. Recurrent topics in Daniel Urda’s work include Gene expression and cancer classification (6 papers), Anomaly Detection Techniques and Applications (5 papers) and Machine Learning in Bioinformatics (5 papers). Daniel Urda is often cited by papers focused on Gene expression and cancer classification (6 papers), Anomaly Detection Techniques and Applications (5 papers) and Machine Learning in Bioinformatics (5 papers). Daniel Urda collaborates with scholars based in Spain, United States and United Kingdom. Daniel Urda's co-authors include J. Andrew Bagnell, Martial Hebert, Nicolas Vandapel, José M. Jerez, Leonardo Franco, Juan Jesús Ruíz-Aguilar, Ignacio J. Turias, Xuehan Xiong, Bernabé Dorronsoro and Rafael Marcos Luque‐Baena and has published in prestigious journals such as PLoS ONE, Sensors and Biochimica et Biophysica Acta (BBA) - General Subjects.

In The Last Decade

Co-authorship network of co-authors of Daniel Urda i

Fields of papers citing papers by Daniel Urda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Daniel Urda

Since Specialization
Citations

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