Daniela Grassi

28 papers receiving 471 citations

Peers

Daniela Grassi
Comparison fields: 5 of 79
  • Behavioral Neuroscience 105
  • Endocrine and Autonomic Systems 71
  • Biological Psychiatry 15
  • Reproductive Medicine 46
  • Cognitive Neuroscience 102
Replace Paul A. S. Sheppard with:
Paul A. S. Sheppard Canada
Jenne M. Westberry United States
Lisa R. Taxier United States
Shannon L. Dean United States
Amy S. Kohtz United States
Valerie L. Hedges United States
Claudia Aguirre United States
S. Kohama United States
B. Lorenz United States
Katsuya Uchida Japan
Daniela Grassi relative to Paul A. S. Sheppard Canada Paul A. S. Sheppard's profile →
Citations per field
00.5×4.3×
Paul A. S. Sheppard · 1×
Citations per year

Countries citing papers authored by Daniela Grassi

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Grassi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016106
2 201748
3 201332
4 202030
5 201029
6 200627
7 201126
8 202026
9 202215
10 201613
11 202312
12 202212
13 201212
14 201911
15 201511
16 201410
17 20199
18 20228
19 20227
20 20227

About Daniela Grassi

Daniela Grassi is a scholar working on Behavioral Neuroscience, Social Psychology, Genetics, Molecular Biology and Endocrine and Autonomic Systems, having authored 31 papers that have together received 474 indexed citations. Recurring topics across this work include Stress Responses and Cortisol (14 papers), Neuroendocrine regulation and behavior (10 papers), Estrogen and related hormone effects (8 papers), Hypothalamic control of reproductive hormones (4 papers), Circadian rhythm and melatonin (4 papers), Hormonal and reproductive studies (2 papers), Epigenetics and DNA Methylation (2 papers) and Emotion and Mood Recognition (2 papers). The work is most often cited by research in Behavioral Neuroscience (105 citations), Endocrine and Autonomic Systems (71 citations), Biological Psychiatry (15 citations), Reproductive Medicine (46 citations) and Cognitive Neuroscience (102 citations). Daniela Grassi has collaborated with scholars based in Spain, Italy and Germany. Frequent co-authors include Luis Miguel García‐Segura, Giancarlo Panzica, Natalia Lagunas, Sara Valencia Garcia, Patrice Fort, Paul‐Antoine Libourel, Michael Lazarus, Pierre‐Hervé Luppi, Helena Pinos and Paloma Collado. Their work appears in journals such as Frontiers in Neuroendocrinology, Endocrinology, Neuroscience, Brain Research and Neuroendocrinology.

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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