G. Gatti

66 total papers · 1.3k total citations
44 papers, 880 citations indexed

About

G. Gatti is a scholar working on Oncology, Epidemiology and Neurology. According to data from OpenAlex, G. Gatti has authored 44 papers receiving a total of 880 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Oncology, 13 papers in Epidemiology and 10 papers in Neurology. Recurrent topics in G. Gatti's work include Neuroendocrine Tumor Research Advances (12 papers), Lung Cancer Research Studies (11 papers) and Neuroblastoma Research and Treatments (9 papers). G. Gatti is often cited by papers focused on Neuroendocrine Tumor Research Advances (12 papers), Lung Cancer Research Studies (11 papers) and Neuroblastoma Research and Treatments (9 papers). G. Gatti collaborates with scholars based in Italy, Switzerland and United Kingdom. G. Gatti's co-authors include Marco Volante, Mauro Papotti, Alberto Angeli, Maria Luisa Sartori, Luisella Righi, Giuseppe Pelosi, R.G. Masera, Federica Massa, Caterina Marchiò and Rossana Cavallo and has published in prestigious journals such as The Lancet, SHILAP Revista de lepidopterología and The Journal of Clinical Endocrinology & Metabolism.

In The Last Decade

G. Gatti

43 papers receiving 867 citations

Author Peers

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

Author						Papers	Cites
G. Gatti	417	385	247	127	100	44	880
Manuela Albertelli	472 1.1×	560 1.5×	336 1.4×	102 0.8×	50 0.5×	66	917
I M Modlin	286 0.7×	270 0.7×	129 0.5×	531 4.2×	114 1.1×	35	923
Hsin-I Ma	231 0.6×	213 0.6×	173 0.7×	81 0.6×	58 0.6×	37	1.0k
G. Willems	345 0.8×	345 0.9×	202 0.8×	466 3.7×	166 1.7×	46	1.0k
Shuhei Morita	153 0.4×	181 0.5×	254 1.0×	197 1.6×	59 0.6×	67	887
Takesaburo Ogata	143 0.3×	143 0.4×	184 0.7×	134 1.1×	134 1.3×	55	833
Aijun Zhang	162 0.4×	197 0.5×	154 0.6×	62 0.5×	101 1.0×	57	892
Eugene Vlodavsky	119 0.3×	167 0.4×	330 1.3×	69 0.5×	141 1.4×	48	847
Hye Ok Kim	165 0.4×	94 0.2×	228 0.9×	142 1.1×	204 2.0×	47	1.0k
Samu Kurki	230 0.6×	78 0.2×	81 0.3×	77 0.6×	131 1.3×	46	731

Countries citing papers authored by G. Gatti

Since Specialization

Citations

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

Fields of papers citing papers by G. Gatti

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of G. Gatti

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