Diego Díez

2.3k total citations
33 papers, 1.7k citations indexed

About

Diego Díez is a scholar working on Molecular Biology, Oncology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Diego Díez has authored 33 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Molecular Biology, 6 papers in Oncology and 5 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Diego Díez's work include Single-cell and spatial transcriptomics (6 papers), Thyroid Disorders and Treatments (5 papers) and Bioinformatics and Genomic Networks (5 papers). Diego Díez is often cited by papers focused on Single-cell and spatial transcriptomics (6 papers), Thyroid Disorders and Treatments (5 papers) and Bioinformatics and Genomic Networks (5 papers). Diego Díez collaborates with scholars based in Japan, Spain and Sweden. Diego Díez's co-authors include Andrew P. Hutchins, Diego Miranda‐Saavedra, Rikinari Hanayama, Juan Bernal, Beatriz Morte, Yuji Miyatake, Takahiro Nishibu, Wataru Nakai, Yoshifusa Sadamura and Takeshi Yoshida and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Diego Díez

32 papers receiving 1.7k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Diego Díez Japan 18 1.0k 348 340 274 142 33 1.7k
Emiliano Giardina Italy 27 905 0.9× 134 0.4× 435 1.3× 120 0.4× 108 0.8× 145 2.2k
Laurent Gros France 24 1.1k 1.1× 171 0.5× 564 1.7× 241 0.9× 418 2.9× 59 2.3k
Xiuli Liu China 24 1.1k 1.0× 246 0.7× 169 0.5× 78 0.3× 177 1.2× 76 1.9k
Mónika Göőz United States 24 754 0.7× 165 0.5× 313 0.9× 83 0.3× 282 2.0× 60 1.8k
Ying Ni United States 25 1.2k 1.2× 434 1.2× 169 0.5× 222 0.8× 305 2.1× 114 2.1k
Juan A. Bernal Spain 19 1.2k 1.1× 223 0.6× 132 0.4× 107 0.4× 259 1.8× 38 1.7k
Takahisa Nakamura Japan 21 1.6k 1.6× 257 0.7× 467 1.4× 66 0.2× 187 1.3× 50 2.3k
Paul R. Mittelstadt United States 22 885 0.9× 269 0.8× 911 2.7× 171 0.6× 417 2.9× 29 1.9k
Rodolfo Iuliano Italy 28 1.7k 1.6× 631 1.8× 519 1.5× 252 0.9× 327 2.3× 75 2.6k
Kathryn P. Burdon Australia 37 1.5k 1.4× 163 0.5× 208 0.6× 220 0.8× 93 0.7× 156 3.9k

Countries citing papers authored by Diego Díez

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Diego Díez

This figure shows the co-authorship network connecting the top 25 collaborators of Diego Díez. A scholar is included among the top collaborators of Diego Díez based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Diego Díez. Diego Díez is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Horimoto, Yoshiya, et al.. (2025). DeepSpaceDB: a spatial transcriptomics atlas for interactive in-depth analysis of tissues and tissue microenvironments. Nucleic Acids Research. 54(D1). D1017–D1030.
2.
Sun, Xin, Shailendra Kumar Singh, Kiyoharu Fukushima, et al.. (2024). Deletion of the mRNA endonuclease Regnase-1 promotes NK cell anti-tumor activity via OCT2-dependent transcription of Ifng. Immunity. 57(6). 1360–1377.e13. 6 indexed citations
3.
Abe, Gabriela L., Soyoung Park, Ponpan Matangkasombut, et al.. (2023). Intercellular crosstalk in adult dental pulp is mediated by heparin-binding growth factors Pleiotrophin and Midkine. BMC Genomics. 24(1). 184–184. 2 indexed citations
4.
Vandenbon, Alexis & Diego Díez. (2023). A universal tool for predicting differentially active features in single-cell and spatial genomics data. Scientific Reports. 13(1). 11830–11830. 3 indexed citations
5.
Teraguchi, Shunsuke, et al.. (2022). Unbiased integration of single cell transcriptome replicates. NAR Genomics and Bioinformatics. 4(1). lqac022–lqac022. 7 indexed citations
6.
Bernal, Juan, Beatriz Morte, & Diego Díez. (2022). Thyroid hormone regulators in human cerebral cortex development. Journal of Endocrinology. 255(3). R27–R36. 18 indexed citations
7.
Díez, Diego, Beatriz Morte, & Juan Bernal. (2021). Single-cell transcriptome profiling of thyroid hormone effectors in the human fetal neocortex: expression of SLCO1C1, DIO2, and THRB in specific cell types. Thyroid. 31(10). 1577–1588. 16 indexed citations
8.
Teraguchi, Shunsuke, Mara Anaís Llamas-Covarrubias, Ana Davila, et al.. (2020). Methods for sequence and structural analysis of B and T cell receptor repertoires. Computational and Structural Biotechnology Journal. 18. 2000–2011. 24 indexed citations
9.
Vandenbon, Alexis & Diego Díez. (2020). A clustering-independent method for finding differentially expressed genes in single-cell transcriptome data. Nature Communications. 11(1). 4318–4318. 55 indexed citations
10.
Vandenbon, Alexis, Diego Díez, Edward Wijaya, et al.. (2017). Mapping circulating serum miRNAs to their immune-related target mRNAs. SHILAP Revista de lepidopterología. Volume 10. 1–9. 4 indexed citations
11.
Nakai, Wataru, Takeshi Yoshida, Diego Díez, et al.. (2016). A novel affinity-based method for the isolation of highly purified extracellular vesicles. Scientific Reports. 6(1). 33935–33935. 378 indexed citations
12.
Díez, Diego, Àlvar Agustí, & Craig E. Wheelock. (2014). Network Analysis in the Investigation of Chronic Respiratory Diseases. From Basics to Application. American Journal of Respiratory and Critical Care Medicine. 190(9). 981–988. 36 indexed citations
13.
Hutchins, Andrew P., Diego Díez, & Diego Miranda‐Saavedra. (2013). Genomic and computational approaches to dissect the mechanisms of STAT3’s universal and cell type-specific functions. PubMed. 2(4). e25097–e25097. 25 indexed citations
14.
Hutchins, Andrew P., Diego Díez, Yoshiko Takahashi, et al.. (2013). Distinct transcriptional regulatory modules underlie STAT3’s cell type-independent and cell type-specific functions. Nucleic Acids Research. 41(4). 2155–2170. 65 indexed citations
15.
Hutchins, Andrew P., et al.. (2013). The Repertoires of Ubiquitinating and Deubiquitinating Enzymes in Eukaryotic Genomes. Molecular Biology and Evolution. 30(5). 1172–1187. 57 indexed citations
16.
Díez, Diego, Susumu Goto, John V. Fahy, et al.. (2012). Network analysis identifies a putative role for the PPAR and type 1 interferon pathways in glucocorticoid actions in asthmatics. BMC Medical Genomics. 5(1). 27–27. 16 indexed citations
17.
Díez, Diego, Francisca Sánchez‐Jiménez, & Juan A. G. Ranea. (2011). Evolutionary expansion of the Ras switch regulatory module in eukaryotes. Nucleic Acids Research. 39(13). 5526–5537. 19 indexed citations
18.
Morte, Beatriz, Diego Díez, Carmen Grijota-Martínez, et al.. (2010). Thyroid Hormone-Regulated Mouse Cerebral Cortex Genes Are Differentially Dependent on the Source of the Hormone: A Study in Monocarboxylate Transporter-8- and Deiodinase-2-Deficient Mice. Endocrinology. 151(5). 2381–2387. 102 indexed citations
19.
Wheelock, Craig E., Åsa M. Wheelock, Shuichi Kawashima, et al.. (2009). Systems biology approaches and pathway tools for investigating cardiovascular disease. Molecular BioSystems. 5(6). 588–602. 69 indexed citations
20.
Díez, Diego, Åsa M. Wheelock, Susumu Goto, et al.. (2009). The use of network analyses for elucidating mechanisms in cardiovascular disease. Molecular BioSystems. 6(2). 289–304. 75 indexed citations

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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