Erick Armingol
Impact in
- Aging top 5%
- Biophysics top 2%
- Cell Image Analysis Techniques
Papers in
-
- Single-cell and spatial transcriptomics 6
- Gene Regulatory Network Analysis 5
- Microbial Metabolic Engineering and Bioproduction 2
- Bioinformatics and Genomic Networks 2
-
- Molecular Communication and Nanonetworks 2
- Co-authors
- Nathan E. Lewis (8 shared papers)Adam Officer (1 shared paper)Olivier Harismendy (1 shared paper)Hratch Baghdassarian (4 shared papers)Eyleen J. O’Rourke (3 shared papers)Araceli Pérez-López (1 shared paper)Rob Knight (1 shared paper)Cameron Martino (1 shared paper)
- Journals
- Nature Reviews Genetics (2 papers)PLoS ONE (1 paper)Cell Reports Methods (1 paper)Nature Genetics (1 paper)PLoS Computational Biology (1 paper)
- Partner nations
- United StatesGermanyChile
In The Last Decade
Erick Armingol
11 papers receiving 1.1k citations
Erick Armingol's Hit Papers
Peers
Comparison fields: 5 of 107
- Aging 41
- Biophysics 131
- Molecular Biology 742
- Immunology 180
- Computational Mathematics 5
Countries citing papers authored by Erick Armingol
This map shows the geographic impact of Erick Armingol'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 Erick Armingol with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Erick Armingol more than expected).
Fields of papers citing papers by Erick Armingol
This network shows the impact of papers produced by Erick Armingol. 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 Erick Armingol. The network helps show where Erick Armingol may publish in the future.
Co-authors
The 25 scholars most cited alongside Erick Armingol, 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 | Deciphering cell–cell interactions and communication from gene expression Hit paper breakdown → | 2020 | 802 |
| 2 | The diversification of methods for studying cell–cell interactions and communication Hit paper breakdown → | 2024 | 90 |
| 3 | 2022 | 59 | |
| 4 | 2022 | 41 | |
| 5 | 2023 | 40 | |
| 6 | 2025 | 22 | |
| 7 | 2018 | 10 | |
| 8 | 2024 | 9 | |
| 9 | 2025 | 2 | |
| 10 | 2022 | 2 | |
| 11 | 2022 | 2 |
About Erick Armingol
Erick Armingol is a scholar working on Molecular Biology, Biomedical Engineering, Aging, Biophysics and Endocrine and Autonomic Systems, having authored 11 papers that have together received 1.1k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (6 papers), Gene Regulatory Network Analysis (5 papers), Molecular Communication and Nanonetworks (2 papers), Microbial Metabolic Engineering and Bioproduction (2 papers), Bioinformatics and Genomic Networks (2 papers), Genetics, Aging, and Longevity in Model Organisms (2 papers), Cell Image Analysis Techniques (2 papers) and Circadian rhythm and melatonin (1 paper). The work is most often cited by research in Aging (41 citations), Biophysics (131 citations), Molecular Biology (742 citations), Immunology (180 citations) and Computational Mathematics (5 citations). Erick Armingol has collaborated with scholars based in United States, Germany and Chile. Frequent co-authors include Nathan E. Lewis, Adam Officer, Olivier Harismendy, Hratch Baghdassarian, Eyleen J. O’Rourke, Araceli Pérez-López, Rob Knight, Cameron Martino, R Waterston and Louis Gevirtzman. Their work appears in journals such as Nature Reviews Genetics, PLoS ONE, Cell Reports Methods, Nature Genetics and PLoS Computational Biology.
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.