Chiara Nicolini

2.0k citations
33 papers · 1.6k indexed · 1 hit paper · h-index 22

Impact in

Papers in

Chiara Nicolini

32 papers receiving 1.5k citations

Hit Papers

The valproic acid-induced rodent model of autism 2017 · 418 citations
4182017202620202023100200300400

Peers

Chiara Nicolini
Comparison fields: 5 of 122
  • Cognitive Neuroscience 460
  • Developmental Neuroscience 90
  • Neurology 122
  • Genetics 341
  • Cellular and Molecular Neuroscience 214
Replace Lina Ji with:
Lina Ji China
Jeremy D. Marks United States
Basil Künnecke Switzerland
Namsoo Kim South Korea
Daniel Coman United States
Talaignair N. Venkatraman United States
Alisa G. Woods United States
Lawrence K. Fung United States
Alice Bertero Italy
Hui‐Yuan Wu China
Chiara Nicolini relative to Lina Ji China Lina Ji's profile →
Citations per field
00.5×1.5×2.4×
Lina Ji · 1×
Citations per year

Countries citing papers authored by Chiara Nicolini

Since Specialization
Citations

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

Fields of papers citing papers by Chiara Nicolini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20246
2 20211
3 20214
4 202049
5 202039
6 20209
7 201922
8 201929
9 20195
10 201833
11
The valproic acid-induced rodent model of autism
Hit paper breakdown →
2017418
12 201730
13 201575
14 201351
15 201278
16 20112
17 20071
18 200661
19 200533
20 200481

About Chiara Nicolini

Chiara Nicolini is a scholar working on Neurology, Neuropsychology and Physiological Psychology, Developmental Neuroscience, Cognitive Neuroscience and Rehabilitation, having authored 33 papers that have together received 1.6k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (7 papers), Transcranial Magnetic Stimulation Studies (7 papers), Lipid Membrane Structure and Behavior (7 papers), Genetics and Neurodevelopmental Disorders (5 papers), Sphingolipid Metabolism and Signaling (5 papers), Autism Spectrum Disorder Research (5 papers), Muscle activation and electromyography studies (4 papers) and Cellular transport and secretion (2 papers). The work is most often cited by research in Cognitive Neuroscience (460 citations), Developmental Neuroscience (90 citations), Neurology (122 citations), Genetics (341 citations) and Cellular and Molecular Neuroscience (214 citations). Chiara Nicolini has collaborated with scholars based in Canada, Germany and United States. Frequent co-authors include Margaret Fahnestock, Roland Winter, Revanur Ravindra, Bernadeta Michalski, Aimee J. Nelson, Wojciech Dzwolak, Martin J. Gibala, Ralf Jansen, Enrico Gratton and Herbert Waldmann. Their work appears in journals such as Neuroscience, Journal of the American Chemical Society, Biophysical Journal, Experimental Neurology and Cortex.

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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2026