Diego Díez
Impact in
- Cancer Research top 5%
- MicroRNA in disease regulation
-
- Thyroid Disorders and Treatments
- Growth Hormone and Insulin-like Growth Factors
Papers in
-
- Single-cell and spatial transcriptomics 6
- Gene expression and cancer classification 5
- Gene Regulatory Network Analysis 4
- Bioinformatics and Genomic Networks 3
- Genomics and Chromatin Dynamics 3
-
- Thyroid Disorders and Treatments 5
- Growth Hormone and Insulin-like Growth Factors 3
- Co-authors
- Diego Miranda‐Saavedra (5 shared papers)Andrew P. Hutchins (5 shared papers)Rikinari Hanayama (2 shared papers)Beatriz Morte (6 shared papers)Juan Bernal (6 shared papers)Yoshifusa Sadamura (1 shared paper)Wataru Nakai (1 shared paper)Takeshi Yoshida (1 shared paper)
In The Last Decade
Diego Díez
33 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 106
- Cancer Research 321
- Endocrinology, Diabetes and Metabolism 273
- Immunology 300
- Molecular Biology 989
- Neurology 101
Countries citing papers authored by Diego Díez
This map shows the geographic impact of Diego Díez'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 Díez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Diego Díez more than expected).
Fields of papers citing papers by Diego Díez
This network shows the impact of papers produced by Diego Díez. 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 Díez. The network helps show where Diego Díez may publish in the future.
Co-authors
The 25 scholars most cited alongside Diego Díez, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 388 | |
| 2 | 2013 | 329 | |
| 3 | 2015 | 160 | |
| 4 | 2010 | 103 | |
| 5 | 2009 | 74 | |
| 6 | 2009 | 69 | |
| 7 | 2011 | 69 | |
| 8 | 2013 | 65 | |
| 9 | 2008 | 62 | |
| 10 | 2010 | 62 | |
| 11 | 2013 | 58 | |
| 12 | 2020 | 55 | |
| 13 | 2014 | 36 | |
| 14 | 2020 | 25 | |
| 15 | 2013 | 25 | |
| 16 | 2013 | 25 | |
| 17 | 2011 | 19 | |
| 18 | 2022 | 18 | |
| 19 | 2012 | 16 | |
| 20 | 2021 | 16 |
About Diego Díez
Diego Díez is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism, Oncology, Immunology and Cancer Research, having authored 33 papers that have together received 1.7k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (6 papers), Gene expression and cancer classification (5 papers), Thyroid Disorders and Treatments (5 papers), Gene Regulatory Network Analysis (4 papers), Bioinformatics and Genomic Networks (3 papers), Growth Hormone and Insulin-like Growth Factors (3 papers), Genomics and Chromatin Dynamics (3 papers) and MicroRNA in disease regulation (3 papers). The work is most often cited by research in Cancer Research (321 citations), Endocrinology, Diabetes and Metabolism (273 citations), Immunology (300 citations), Molecular Biology (989 citations) and Neurology (101 citations). Diego Díez has collaborated with scholars based in Japan, Spain and Sweden. Frequent co-authors include Diego Miranda‐Saavedra, Andrew P. Hutchins, Rikinari Hanayama, Beatriz Morte, Juan Bernal, Yoshifusa Sadamura, Wataru Nakai, Takeshi Yoshida, Takahiro Nishibu and Yuji Miyatake. Their work appears in journals such as Nucleic Acids Research, Endocrinology, Bioinformatics, Scientific Reports and Molecular BioSystems.
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.