Giulia Pregno

1.2k citations
7 papers · 739 · h-index 7

Impact in

  • Genetics top 10%
    • Genomic variations and chromosomal abnormalities
    • Genomics and Rare Diseases
    • Genetics and Neurodevelopmental Disorders
    • Cancer Genomics and Diagnostics

Papers in

Giulia Pregno

7 papers receiving 717 citations

Peers

Giulia Pregno
Comparison fields: 5 of 81
  • Genetics 377
  • Cancer Research 94
  • Molecular Biology 401
  • Pediatrics, Perinatology and Child Health 63
  • Plant Science 127
Replace Djie Tjwan Thung with:
Djie Tjwan Thung Netherlands
Caroline W. Antolik United States
Nelson T. Chuang United States
Jennifer McCallum United States
Erşen Kavak Türkiye
Anwyn Apedaile United Kingdom
Violet Gelowani United States
Liesbeth Backx Belgium
Diane M. Bushman United States
Marc Trimborn Germany
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Citations per field
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Djie Tjwan Thung · 1×
Citations per year

Countries citing papers authored by Giulia Pregno

Since Specialization
Citations

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

Fields of papers citing papers by Giulia Pregno

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

7 of 7 papers shown
#Work
1 2017286
2 2016240
3 2017136
4 201128
5 202023
6 201315
7 201111

About Giulia Pregno

Giulia Pregno is a scholar working on Cellular and Molecular Neuroscience, Neurology, Genetics, Cancer Research and Molecular Biology, having authored 7 papers that have together received 739 indexed citations. Recurring topics across this work include Genomic variations and chromosomal abnormalities (2 papers), Neuroscience and Neuropharmacology Research (2 papers), Cancer Genomics and Diagnostics (1 paper), Genomics and Phylogenetic Studies (1 paper), RNA regulation and disease (1 paper), Adipose Tissue and Metabolism (1 paper), Chromosomal and Genetic Variations (1 paper) and Algorithms and Data Compression (1 paper). The work is most often cited by research in Genetics (377 citations), Cancer Research (94 citations), Molecular Biology (401 citations), Pediatrics, Perinatology and Child Health (63 citations) and Plant Science (127 citations). Giulia Pregno has collaborated with scholars based in Italy, United States and Germany. Frequent co-authors include Joep de Ligt, Michael E. Talkowski, Ivo J. Renkens, Daniela Francesca Giachino, Markus J. van Roosmalen, Jerome Korzelius, Jeroen de Ridder, Tobias Marschall, Ewart de Bruijn and Edwin P. J. G. Cuppen. Their work appears in journals such as Frontiers in Cellular Neuroscience, Nature Communications, BMC Neuroscience, Nature Genetics and Genome 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.

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