Daniel Hidalgo

1.1k citations
21 papers · 731 · h-index 11

Impact in

Papers in

    • Erythrocyte Function and Pathophysiology 10
    • Genomics and Chromatin Dynamics 4
    • RNA Research and Splicing 3
    • Epigenetics and DNA Methylation 2
    • Melanoma and MAPK Pathways 2

Daniel Hidalgo

20 papers receiving 727 citations

Peers

Daniel Hidalgo
Comparison fields: 5 of 88
  • Hematology 154
  • Genetics 139
  • Physiology 231
  • Immunology 144
  • Molecular Biology 399
Replace Raymond T. Doty with:
Raymond T. Doty United States
Alexander Groß Germany
Nicki Gray United Kingdom
Felix A. Klein Germany
Maria Schell United States
Stephan Kadauke United States
A. Marieke Oudelaar United Kingdom
Matthew R. Huska Germany
Akie Maehara Japan
Akinori Kawamura Japan
Daniel Hidalgo relative to Raymond T. Doty United States Raymond T. Doty's profile →
Citations per field
00.5×2.8×
Raymond T. Doty · 1×
Citations per year

Countries citing papers authored by Daniel Hidalgo

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Hidalgo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Hidalgo. 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 Daniel Hidalgo. The network helps show where Daniel Hidalgo may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018253
2 2011110
3 202082
4 201742
5 201139
6 201138
7 201435
8 201235
9 202132
10 201820
11 202011
12 20228
13 20165
14 20175
15 20195
16 20214
17 20212
18 20232
19 20242
20 20171

About Daniel Hidalgo

Daniel Hidalgo is a scholar working on Physiology, Molecular Biology, Cell Biology, Plant Science and Oncology, having authored 21 papers that have together received 731 indexed citations. Recurring topics across this work include Erythrocyte Function and Pathophysiology (10 papers), Genomics and Chromatin Dynamics (4 papers), RNA Research and Splicing (3 papers), Cytokine Signaling Pathways and Interactions (3 papers), Immune Cell Function and Interaction (2 papers), Hippo pathway signaling and YAP/TAZ (2 papers), Epigenetics and DNA Methylation (2 papers) and Melanoma and MAPK Pathways (2 papers). The work is most often cited by research in Hematology (154 citations), Genetics (139 citations), Physiology (231 citations), Immunology (144 citations) and Molecular Biology (399 citations). Daniel Hidalgo has collaborated with scholars based in United States, Netherlands and United Kingdom. Frequent co-authors include Merav Socolovsky, Miroslav Koulnis, Ermelinda Porpiglia, Yung Hwang, Ramona Pop, Allon M. Klein, Rapolas Žilionis, Betsabeh Khoramian Tusi, Jun R. Huh and Samuel L. Wolock. Their work appears in journals such as Blood, Cancer Research, Journal of Visualized Experiments, Nature Communications and Science Advances.

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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