Daniela Curti

2.3k citations
63 papers · 1.9k indexed · h-index 27

Impact in

Papers in

Daniela Curti

63 papers receiving 1.9k citations

Peers

Daniela Curti
Comparison fields: 5 of 100
  • Biological Psychiatry 124
  • Developmental Neuroscience 153
  • Cellular and Molecular Neuroscience 498
  • Neurology 344
  • Neurology 179
Replace Chien‐liang Glenn Lin with:
Chien‐liang Glenn Lin United States
Akiko Furuta Japan
Kerry Cormier United States
Emilio Fernández Spain
Takako Niikura Japan
Patricia A. Trimmer United States
Bernd O. Evert Germany
Ding‐I Yang Taiwan
Robert B. Nelson United States
Ángeles Martín‐Requero Spain
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Citations per field
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Citations per year

Countries citing papers authored by Daniela Curti

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Curti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003207
2 1992113
3 2013113
4 1996108
5 199690
6 199779
7 199876
8 201269
9 199768
10 199057
11 201851
12 200646
13 199946
14 199144
15 201143
16 198943
17 200242
18 200140
19 201338
20 201333

About Daniela Curti

Daniela Curti is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Physiology, Neurology and Clinical Biochemistry, having authored 63 papers that have together received 1.9k indexed citations. Recurring topics across this work include Mitochondrial Function and Pathology (21 papers), Pharmacological Receptor Mechanisms and Effects (14 papers), Neuroscience and Neuropharmacology Research (14 papers), Amyotrophic Lateral Sclerosis Research (10 papers), Metabolism and Genetic Disorders (10 papers), Diet and metabolism studies (8 papers), Receptor Mechanisms and Signaling (7 papers) and Cholinesterase and Neurodegenerative Diseases (7 papers). The work is most often cited by research in Biological Psychiatry (124 citations), Developmental Neuroscience (153 citations), Cellular and Molecular Neuroscience (498 citations), Neurology (344 citations) and Neurology (179 citations). Daniela Curti has collaborated with scholars based in Italy, Germany and United Kingdom. Frequent co-authors include G. Benzi, Fulvio Marzatico, F. Dagani, R. M. Marchbanks, R. F. Villa, S. A. Whatley, O. Pastoris, Daniela Rossi, Simona Collina and Marco Biggiogera. Their work appears in journals such as Neurochemical Research, Biochemical Pharmacology, Neurology, Mechanisms of Ageing and Development and Experimental Gerontology.

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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