Fabio Rigat

48 total papers · 1.3k total citations
23 papers, 603 citations indexed

About

Fabio Rigat is a scholar working on Epidemiology, Molecular Biology and Cognitive Neuroscience. According to data from OpenAlex, Fabio Rigat has authored 23 papers receiving a total of 603 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Epidemiology, 5 papers in Molecular Biology and 4 papers in Cognitive Neuroscience. Recurrent topics in Fabio Rigat's work include Pneumonia and Respiratory Infections (5 papers), Statistical Methods and Inference (3 papers) and Bayesian Methods and Mixture Models (3 papers). Fabio Rigat is often cited by papers focused on Pneumonia and Respiratory Infections (5 papers), Statistical Methods and Inference (3 papers) and Bayesian Methods and Mixture Models (3 papers). Fabio Rigat collaborates with scholars based in United Kingdom, Italy and United States. Fabio Rigat's co-authors include Rino Rappuoli, Mariagrazia Pizza, Duccio Medini, Alessia Biolchi, Ray Borrow, Marzia Monica Giuliani, Jay Lucidarme, Jamie Findlow, Alfredo Pezzicoli and Franco Laghi‐Pasini and has published in prestigious journals such as Blood, Technometrics and Clinical Infectious Diseases.

In The Last Decade

Fabio Rigat

22 papers receiving 577 citations

Author Peers

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

Author						Papers	Cites
Fabio Rigat	261	152	118	107	92	23	603
Martin Lopez	177 0.7×	14 0.1×	170 1.4×	161 1.5×	19 0.2×	17	631
Н. Т. Райхлин	156 0.6×	15 0.1×	157 1.3×	79 0.7×	21 0.2×	26	596
Maya D. Srivastava	80 0.3×	52 0.3×	125 1.1×	221 2.1×	25 0.3×	32	683
K Hasegawa	92 0.4×	72 0.5×	72 0.6×	174 1.6×	45 0.5×	35	541
Helen Maureen Massa	167 0.6×	111 0.7×	119 1.0×	30 0.3×	9 0.1×	30	696
Bin Li	112 0.4×	29 0.2×	48 0.4×	29 0.3×	15 0.2×	45	599
Aidan O’Brien	184 0.7×	15 0.1×	50 0.4×	52 0.5×	25 0.3×	25	516
A Yamane	147 0.6×	50 0.3×	161 1.4×	145 1.4×	9 0.1×	34	668
Nicoline Schiess	84 0.3×	38 0.3×	108 0.9×	49 0.5×	15 0.2×	34	600
Xiwen Gao	54 0.2×	82 0.5×	247 2.1×	31 0.3×	7 0.1×	30	515

Countries citing papers authored by Fabio Rigat

Since Specialization

Citations

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

Fields of papers citing papers by Fabio Rigat

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fabio Rigat

This figure shows the co-authorship network connecting the top 25 collaborators of Fabio Rigat. A scholar is included among the top collaborators of Fabio Rigat 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 Fabio Rigat. Fabio Rigat 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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