Daniela Spampinato

1.4k citations
17 papers · 1.1k · h-index 12

Impact in

Papers in

    • Metabolism, Diabetes, and Cancer 8
    • Protein Kinase Regulation and GTPase Signaling 3
    • Peroxisome Proliferator-Activated Receptors 1
    • Pancreatic function and diabetes 5

Daniela Spampinato

17 papers receiving 1.1k citations

Peers

Daniela Spampinato
Comparison fields: 5 of 73
  • Endocrinology, Diabetes and Metabolism 292
  • Physiology 48
  • Physiology 231
  • Epidemiology 286
  • Surgery 294
Replace Chien-Ping Liang with:
Chien-Ping Liang United States
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Kun Wook Chung South Korea
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Citations per field
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Citations per year

Countries citing papers authored by Daniela Spampinato

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Spampinato

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 2005314
2 2007236
3 2002145
4 2001126
5 200159
6 200148
7 200341
8 200737
9 199926
10 200424
11 200716
12 200014
13 200011
14 200310
15 20065
16 20002
17 20001

About Daniela Spampinato

Daniela Spampinato is a scholar working on Molecular Biology, Surgery, Epidemiology, Endocrinology, Diabetes and Metabolism and Cell Biology, having authored 17 papers that have together received 1.1k indexed citations. Recurring topics across this work include Metabolism, Diabetes, and Cancer (8 papers), Pancreatic function and diabetes (5 papers), Growth Hormone and Insulin-like Growth Factors (3 papers), Liver Disease Diagnosis and Treatment (3 papers), Protein Kinase Regulation and GTPase Signaling (3 papers), Adipokines, Inflammation, and Metabolic Diseases (2 papers), Peroxisome Proliferator-Activated Receptors (1 paper) and Hyperglycemia and glycemic control in critically ill and hospitalized patients (1 paper). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (292 citations), Physiology (48 citations), Physiology (231 citations), Epidemiology (286 citations) and Surgery (294 citations). Daniela Spampinato has collaborated with scholars based in Italy, United States and Czechia. Frequent co-authors include Francesco Purrello, Agata Maria Rabuazzo, Salvatore Piro, Vincenzo Trischitta, Lucia Frittitta, Riccardo Vigneri, Rosa Di Paola, Antonio Pizzuti, M. Anello and L. Spadaro. Their work appears in journals such as The Journal of Clinical Endocrinology & Metabolism, Nutrition Metabolism and Cardiovascular Diseases, Diabetes, Diabetes/Metabolism Research and Reviews and Digestive and Liver Disease.

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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