Flavio Piva

33 total papers · 868 total citations
26 papers, 739 citations indexed

About

Flavio Piva is a scholar working on Reproductive Medicine, Cellular and Molecular Neuroscience and Molecular Biology. According to data from OpenAlex, Flavio Piva has authored 26 papers receiving a total of 739 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Reproductive Medicine, 11 papers in Cellular and Molecular Neuroscience and 8 papers in Molecular Biology. Recurrent topics in Flavio Piva's work include Hypothalamic control of reproductive hormones (12 papers), Neuropeptides and Animal Physiology (9 papers) and Stress Responses and Cortisol (8 papers). Flavio Piva is often cited by papers focused on Hypothalamic control of reproductive hormones (12 papers), Neuropeptides and Animal Physiology (9 papers) and Stress Responses and Cortisol (8 papers). Flavio Piva collaborates with scholars based in Italy, Sweden and Poland. Flavio Piva's co-authors include Roberto Maggi, Patrízia Limonta, Luciano Martini, D. Dondi, Federica Pimpinelli, Anna Cariboni, Margherita Piccolella, Alberto E. Panerai, Elena I. Rugarli and Sophia A. Colamarino and has published in prestigious journals such as Brain Research, Endocrinology and Human Molecular Genetics.

In The Last Decade

Flavio Piva

25 papers receiving 732 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Flavio Piva	309	258	221	165	162	26	739
J.G. Ondo	266 0.9×	263 1.0×	157 0.7×	188 1.1×	231 1.4×	36	799
Yoshihito Okamura	156 0.5×	181 0.7×	160 0.7×	107 0.6×	131 0.8×	19	640
Irvin E. Lawrence	224 0.7×	303 1.2×	169 0.8×	72 0.4×	291 1.8×	32	904
G Sétáló	186 0.6×	223 0.9×	160 0.7×	98 0.6×	130 0.8×	25	647
Laura S. Lubbers	186 0.6×	175 0.7×	222 1.0×	130 0.8×	105 0.6×	35	819
Khushdev K. Thind	277 0.9×	305 1.2×	107 0.5×	136 0.8×	188 1.2×	19	662
B Flerkó	149 0.5×	326 1.3×	126 0.6×	129 0.8×	181 1.1×	46	737
M. Ferin	169 0.5×	299 1.2×	99 0.4×	152 0.9×	186 1.1×	15	712
Marie‐Christine Tonon	346 1.1×	76 0.3×	210 1.0×	144 0.9×	124 0.8×	23	831
Ann‐Judith Silverman	204 0.7×	443 1.7×	119 0.5×	114 0.7×	219 1.4×	18	895

Countries citing papers authored by Flavio Piva

Since Specialization

Citations

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

Fields of papers citing papers by Flavio Piva

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Flavio Piva

This figure shows the co-authorship network connecting the top 25 collaborators of Flavio Piva. A scholar is included among the top collaborators of Flavio Piva based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Flavio Piva. Flavio Piva is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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