Diego Alonso‐López

1.7k citations
15 papers · 543 · h-index 9

Impact in

    • Cancer-related molecular mechanisms research
    • Bioinformatics and Genomic Networks
    • RNA Research and Splicing
    • Microbial Metabolic Engineering and Bioproduction
    • RNA modifications and cancer
    • Gene expression and cancer classification

Papers in

    • Bioinformatics and Genomic Networks 4
    • Immune Cell Function and Interaction 4
    • T-cell and B-cell Immunology 2

Diego Alonso‐López

14 papers receiving 536 citations

Peers

Diego Alonso‐López
Comparison fields: 5 of 81
  • Cancer Research 71
  • Molecular Biology 327
  • Oncology 84
  • Computational Theory and Mathematics 52
  • Immunology 53
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Citations per field
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Citations per year

Countries citing papers authored by Diego Alonso‐López

Since Specialization
Citations

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

Fields of papers citing papers by Diego Alonso‐López

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Diego Alonso‐López. 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 Diego Alonso‐López. The network helps show where Diego Alonso‐López may publish in the future.

Co-authors

The 25 scholars most cited alongside Diego Alonso‐López, 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 Diego Alonso‐López Line = papers co-authored together Diego Alonso‐López links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 2020141
2 2019112
3 201689
4 201573
5 201628
6 201826
7 202120
8 202015
9 201715
10 20198
11 20245
12 20204
13 20204
14 20183
15 20250

About Diego Alonso‐López

Diego Alonso‐López is a scholar working on Molecular Biology, Immunology, Oncology, Genetics and Computational Theory and Mathematics, having authored 15 papers that have together received 543 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (4 papers), Immune Cell Function and Interaction (4 papers), T-cell and B-cell Immunology (2 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (2 papers), Computational Drug Discovery Methods (2 papers), CAR-T cell therapy research (2 papers), Acute Myeloid Leukemia Research (1 paper) and Pharmacogenetics and Drug Metabolism (1 paper). The work is most often cited by research in Cancer Research (71 citations), Molecular Biology (327 citations), Oncology (84 citations), Computational Theory and Mathematics (52 citations) and Immunology (53 citations). Diego Alonso‐López has collaborated with scholars based in Spain, United States and Puerto Rico. Frequent co-authors include Javier De Las Rivas, Miguel A. Gutiérrez, Elizabeta A. Rojas, F.J. Burguillo, Luís A. Corchete, Norma C. Gutiérrez, L. Lambourne, Francisco Campos‐Laborie, Marc Vidal and Michael A. Calderwood. Their work appears in journals such as Science Signaling, British Journal of Dermatology, Cell Reports, Platelets and Nucleic Acids Research.

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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