Bruno Aranda
Impact in
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- Advanced Proteomics Techniques and Applications
- Mass Spectrometry Techniques and Applications
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- Bioinformatics and Genomic Networks
- Biomedical Text Mining and Ontologies
- Metabolomics and Mass Spectrometry Studies
- Microbial Metabolic Engineering and Bioproduction
- Gene expression and cancer classification
Papers in
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- Biomedical Text Mining and Ontologies 3
- Bioinformatics and Genomic Networks 2
- Microbial Metabolic Engineering and Bioproduction 1
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- Computational Drug Discovery Methods 2
- Co-authors
- Henning Hermjakob (4 shared papers)Sandra Orchard (3 shared papers)Gavin Koh (1 shared paper)Pablo Porras (1 shared paper)Samuel Kerrien (2 shared papers)Florian Reisinger (1 shared paper)Lennart Martens (1 shared paper)Luisa Montecchi‐Palazzi (1 shared paper)
- Journals
- Current Protocols in Protein Science (1 paper)Genome biology (1 paper)Journal of Proteome Research (1 paper)PROTEOMICS (1 paper)
- Partner nations
- United KingdomRussiaItaly
In The Last Decade
Bruno Aranda
4 papers receiving 200 citations
Peers
Comparison fields: 5 of 59
- Spectroscopy 42
- Molecular Biology 167
- Computational Theory and Mathematics 22
- Structural Biology 1
- Cell Biology 11
Countries citing papers authored by Bruno Aranda
This map shows the geographic impact of Bruno Aranda'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 Bruno Aranda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bruno Aranda more than expected).
Fields of papers citing papers by Bruno Aranda
This network shows the impact of papers produced by Bruno Aranda. 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 Bruno Aranda. The network helps show where Bruno Aranda may publish in the future.
Co-authors
The 19 scholars most cited alongside Bruno Aranda, 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 | 2012 | 135 | |
| 2 | 2009 | 42 | |
| 3 | 2008 | 19 | |
| 4 | 2010 | 5 |
About Bruno Aranda
Bruno Aranda is a scholar working on Molecular Biology, Computational Theory and Mathematics, Artificial Intelligence, Spectroscopy and Infectious Diseases, having authored 4 papers that have together received 201 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (3 papers), Bioinformatics and Genomic Networks (2 papers), Computational Drug Discovery Methods (2 papers), Advanced Proteomics Techniques and Applications (1 paper), Semantic Web and Ontologies (1 paper) and Microbial Metabolic Engineering and Bioproduction (1 paper). The work is most often cited by research in Spectroscopy (42 citations), Molecular Biology (167 citations), Computational Theory and Mathematics (22 citations), Structural Biology (1 citation) and Cell Biology (11 citations). Bruno Aranda has collaborated with scholars based in United Kingdom, Russia and Italy. Frequent co-authors include Henning Hermjakob, Sandra Orchard, Gavin Koh, Pablo Porras, Samuel Kerrien, Florian Reisinger, Lennart Martens, Luisa Montecchi‐Palazzi, Andrew R. Jones and Jyoti Khadake. Their work appears in journals such as Current Protocols in Protein Science, Genome biology, Journal of Proteome Research and PROTEOMICS.
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.