Eric Alcaide

412 citations
4 papers · 31 · h-index 2

Impact in

    • Protein Structure and Dynamics
    • RNA and protein synthesis mechanisms
    • Machine Learning in Bioinformatics
    • RNA modifications and cancer
    • Chemical Synthesis and Analysis
    • RNA Research and Splicing

Papers in

Eric Alcaide

3 papers receiving 31 citations

Peers

Eric Alcaide
Comparison fields: 5 of 27
  • Structural Biology 1
  • Molecular Biology 17
  • Virology 1
  • Molecular Medicine 1
  • Computational Theory and Mathematics 3
Replace Chloé Dequeker with:
Chloé Dequeker France
Xinhao Zhuang China
Miles W. Mee Canada
Lucrezia Catapano United Kingdom
Rodrigo Mora-Rodríguez Costa Rica
B. Seychell Germany
Sachin Kadyan United States
Flavia Corsi Austria
Sudhagar Samydurai Singapore
Chloe Hsu United States
Eric Alcaide relative to Chloé Dequeker France Chloé Dequeker's profile →
Citations per field
00.5×10×15×
Chloé Dequeker · 1×
Citations per year

Countries citing papers authored by Eric Alcaide

Since Specialization
Citations

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

Fields of papers citing papers by Eric Alcaide

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside Eric Alcaide, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Eric Alcaide Line = papers co-authored together Eric Alcaide links everyone, so they are left out of the graph.

All Works

4 of 4 papers shown

About Eric Alcaide

Eric Alcaide is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Safety, Risk, Reliability and Quality and Software, having authored 4 papers that have together received 31 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (3 papers), Computational Drug Discovery Methods (2 papers), Enzyme Structure and Function (2 papers), Genomics and Phylogenetic Studies (1 paper), Software Reliability and Analysis Research (1 paper), Software Testing and Debugging Techniques (1 paper), Safety Systems Engineering in Autonomy (1 paper) and RNA and protein synthesis mechanisms (1 paper). The work is most often cited by research in Structural Biology (1 citation), Molecular Biology (17 citations), Virology (1 citation), Molecular Medicine (1 citation) and Computational Theory and Mathematics (3 citations). Eric Alcaide has collaborated with scholars based in Spain, United Kingdom and China. Frequent co-authors include A.S. Dore, Prakash Rucktooa, Thomas J. Lane, C.D.O. Cooper, Sergey Bartunov, S. Skerratt, Guolin Ke, E Weinan, Huaqing Huang and Ziyao Li. Their work appears in journals such as Software Quality Journal, Journal of Computational Chemistry, Current Opinion in Structural Biology and Journal of Chemical Information and Modeling.

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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