Diego Acosta‐Alvear
- Cell Biology top 0.5%
- Endoplasmic Reticulum Stress and Disease 16
- Aging top 2%
- Molecular Biology top 5%
- RNA regulation and disease 7
- Ubiquitin and proteasome pathways 5
- Photosynthetic Processes and Mechanisms 3
- CRISPR and Genetic Engineering 3
- Epidemiology top 5%
- Autophagy in Disease and Therapy 3
- Immunology top 10%
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- Transgenic Plants and Applications 4
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- Pancreatic function and diabetes 4
- Co-authors
- Peter WalterBrian David DynlachtAlexandre BlaisMary TsikitisYuval KlugerG Elif KaragözCarolina AriasAvi Ashkenazi
- Cited by
- Cell BiologyAgingMolecular Biology
- Journals
- Science (1 paper)Proceedings of the National Academy of Sciences (1 paper)Journal of Clinical Investigation (1 paper)
- Partner nations
- United StatesGermanyCanada
In The Last Decade
Diego Acosta‐Alvear
28 papers receiving 3.3k citations
Hit Papers
Peers
Comparison fields: 5 of 105
- Cell Biology 1.8k
- Aging 99
- Molecular Biology 2.1k
- Epidemiology 922
- Immunology 348
Countries citing papers authored by Diego Acosta‐Alvear
This map shows the geographic impact of Diego Acosta‐Alvear'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 Acosta‐Alvear with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Diego Acosta‐Alvear more than expected).
Fields of papers citing papers by Diego Acosta‐Alvear
This network shows the impact of papers produced by Diego Acosta‐Alvear. 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 Acosta‐Alvear. The network helps show where Diego Acosta‐Alvear may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Diego Acosta‐Alvear, 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 | 2025 | 3 | |
| 2 | 2024 | 29 | |
| 3 | 2024 | 3 | |
| 4 | 2023 | 11 | |
| 5 | 2022 | 28 | |
| 6 | 2022 | 0 | |
| 7 | 2021 | 1 | |
| 8 | 2020 | 17 | |
| 9 | 2019 | 1 | |
| 10 | 2019 | 208 | |
| 11 | 2018 | 71 | |
| 12 | 2017 | 162 | |
| 13 | 2017 | 155 | |
| 14 | 2016 | 83 | |
| 15 | 2015 | 101 | |
| 16 | 2015 | 35 | |
| 17 | Opposing unfolded-protein-response signals converge on death receptor 5 to control apoptosisbreakdown → | 2014 | 447 |
| 18 | 2009 | 51 | |
| 19 | XBP1 Controls Diverse Cell Type- and Condition-Specific Transcriptional Regulatory Networksbreakdown → | 2007 | 665 |
| 20 | 2005 | 362 |
About Diego Acosta‐Alvear
Diego Acosta‐Alvear is a scholar working on Cell Biology, Biotechnology and Aging, having authored 29 papers that have together received 3.4k indexed citations. Recurring topics across this work include Endoplasmic Reticulum Stress and Disease (16 papers), RNA regulation and disease (7 papers), Ubiquitin and proteasome pathways (5 papers), Transgenic Plants and Applications (4 papers), Pancreatic function and diabetes (4 papers), Photosynthetic Processes and Mechanisms (3 papers), Autophagy in Disease and Therapy (3 papers) and CRISPR and Genetic Engineering (3 papers). The work is most often cited by research in Cell Biology (1.8k citations), Aging (99 citations) and Molecular Biology (2.1k citations). Diego Acosta‐Alvear has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include Peter Walter, Brian David Dynlacht, Alexandre Blais, Mary Tsikitis, Yuval Kluger, G Elif Karagöz, Carolina Arias, Avi Ashkenazi, Nathan H. Lents and Yiming Zhou. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Journal of Clinical Investigation.
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.