Daniel Cerdán-Vélez
Impact in
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- RNA and protein synthesis mechanisms
- RNA modifications and cancer
- RNA Research and Splicing
- Genomics and Phylogenetic Studies
- Machine Learning in Bioinformatics
- Protein Structure and Dynamics
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- Genomics and Rare Diseases
Papers in
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- RNA modifications and cancer 3
- Machine Learning in Bioinformatics 3
- RNA and protein synthesis mechanisms 3
- Genomics and Phylogenetic Studies 2
- Congenital heart defects research 1
- Genetics 2
- Genetics and Neurodevelopmental Disorders 1
- Genomics and Rare Diseases 1
- Animal Genetics and Reproduction 1
- Co-authors
- Michael L. Tress (6 shared papers)Jesús Vázquez (3 shared papers)José Manuel Rodrı́guez (2 shared papers)Fernando Campo del Pozo (1 shared paper)Tomás Di Domenico (1 shared paper)Laura Martínez Gómez (2 shared papers)Federico Abascal (2 shared papers)Enrique Calvo (1 shared paper)
- Journals
- Nucleic Acids Research (2 papers)Genome Biology and Evolution (1 paper)BMC Genomics (1 paper)Database (1 paper)Bioinformatics Advances (1 paper)
- Partner nations
- SpainUnited Kingdom
In The Last Decade
Daniel Cerdán-Vélez
5 papers receiving 54 citations
Peers
Comparison fields: 5 of 15
- Molecular Biology 41
- Genetics 10
- Cancer Research 5
- Computational Theory and Mathematics 3
- Spectroscopy 3
Countries citing papers authored by Daniel Cerdán-Vélez
This map shows the geographic impact of Daniel Cerdán-Vélez'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 Cerdán-Vélez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Cerdán-Vélez more than expected).
Fields of papers citing papers by Daniel Cerdán-Vélez
This network shows the impact of papers produced by Daniel Cerdán-Vélez. 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 Cerdán-Vélez. The network helps show where Daniel Cerdán-Vélez may publish in the future.
Co-authors
The 9 scholars most cited alongside Daniel Cerdán-Vélez, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 37 | |
| 2 | 2024 | 5 | |
| 3 | 2022 | 5 | |
| 4 | 2024 | 5 | |
| 5 | 2025 | 2 | |
| 6 | 2025 | 0 |
About Daniel Cerdán-Vélez
Daniel Cerdán-Vélez is a scholar working on Molecular Biology, Genetics, Infectious Diseases, Organic Chemistry and Surgery, having authored 6 papers that have together received 54 indexed citations. Recurring topics across this work include RNA modifications and cancer (3 papers), Machine Learning in Bioinformatics (3 papers), RNA and protein synthesis mechanisms (3 papers), Genomics and Phylogenetic Studies (2 papers), Genetics and Neurodevelopmental Disorders (1 paper), Genomics and Rare Diseases (1 paper), Congenital heart defects research (1 paper) and Animal Genetics and Reproduction (1 paper). The work is most often cited by research in Molecular Biology (41 citations), Genetics (10 citations), Cancer Research (5 citations), Computational Theory and Mathematics (3 citations) and Spectroscopy (3 citations). Daniel Cerdán-Vélez has collaborated with scholars based in Spain and United Kingdom. Frequent co-authors include Michael L. Tress, Jesús Vázquez, José Manuel Rodrı́guez, Fernando Campo del Pozo, Tomás Di Domenico, Laura Martínez Gómez, Federico Abascal, Enrique Calvo and Federico Abascal. Their work appears in journals such as Nucleic Acids Research, Genome Biology and Evolution, BMC Genomics, Database and Bioinformatics Advances.
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.