G. A. Danieli

1.1k citations
37 papers · 804 · h-index 15

Impact in

Papers in

G. A. Danieli

36 papers receiving 780 citations

Peers

G. A. Danieli
Comparison fields: 5 of 81
  • Cardiology and Cardiovascular Medicine 328
  • Cellular and Molecular Neuroscience 152
  • Molecular Biology 538
  • Orthopedics and Sports Medicine 61
  • Genetics 58
Replace Paolo Laveder with:
Paolo Laveder Italy
Ingrid Pinset-Härström France
Mayana Zatz Brazil
Jeroen Vreijling Netherlands
David F. Daggett United States
Z X Lin United States
Svetlana Gorokhova France
Sabrina Batonnet‐Pichon France
Aiping Du United States
Douglas E. Albrecht United States
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Citations per field
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Citations per year

Countries citing papers authored by G. A. Danieli

Since Specialization
Citations

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

Fields of papers citing papers by G. A. Danieli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by G. A. Danieli. 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 G. A. Danieli. The network helps show where G. A. Danieli may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1995145
2 2001103
3 199994
4 199243
5 199841
6 199638
7 196537
8 198731
9 199126
10 199222
11 200121
12 200320
13 197215
14 199314
15 199914
16 197714
17 198713
18 199411
19 198411
20 199411

About G. A. Danieli

G. A. Danieli is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Genetics, Cardiology and Cardiovascular Medicine and Genetics, having authored 37 papers that have together received 804 indexed citations. Recurring topics across this work include Muscle Physiology and Disorders (14 papers), Cardiomyopathy and Myosin Studies (6 papers), Genetic Neurodegenerative Diseases (6 papers), Hereditary Neurological Disorders (5 papers), Neurogenetic and Muscular Disorders Research (5 papers), RNA Research and Splicing (3 papers), RNA regulation and disease (3 papers) and Adipose Tissue and Metabolism (3 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (328 citations), Cellular and Molecular Neuroscience (152 citations), Molecular Biology (538 citations), Orthopedics and Sports Medicine (61 citations) and Genetics (58 citations). G. A. Danieli has collaborated with scholars based in Italy, United States and Switzerland. Frequent co-authors include C. Angelini, Stefania Bortoluzzi, Chiara Romualdi, Gaetano Thiene, Paola Melacini, Natascia Tiso, Alessandra Rampazzo, Andrea Nava, Maria Luisa Mostacciuolo and Elisa Vian. Their work appears in journals such as Human Genetics, Neuromuscular Disorders, Journal of Medical Genetics, Cellular and Molecular Life Sciences and Genetica.

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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