Monica Galliano

3.7k citations
103 papers · 3.1k indexed · 1 hit paper · h-index 29

Monica Galliano

103 papers receiving 3.1k citations

Hit Papers

The extraordinary ligand binding properties of human seru...8942005202620122019250500750

Peers

Monica Galliano
Comparison fields: 5 of 127
  • Molecular Biology 2.3k
  • Cell Biology 466
  • Spectroscopy 432
  • Oncology 558
  • Biochemistry 147
Replace Victor Tuan Giam Chuang with:
Victor Tuan Giam Chuang Japan
Gabriella Fanali Italy
Shigetoshi Sugio Japan
Mark E. McComb United States
Kohji Noguchi Japan
Tomáš Vaisar United States
Brian B. Hasinoff Canada
László G. Boros United States
Mikhail S. Shchepinov United States
Athanassios Giannis Germany
Monica Galliano relative to Victor Tuan Giam Chuang Japan Victor Tuan Giam Chuang's profile →
Citations per field
00.5×1.5×
Victor Tuan Giam Chuang · 1×
Citations per year

Countries citing papers authored by Monica Galliano

Since Specialization
Citations

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

Fields of papers citing papers by Monica Galliano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20201
2 201812
3 201610
4 20164
5 201359
6 201326
7 20118
8 201149
9 200935
10 200850
11 200765
12 200720
13 200412
14 200224
15 200216
16 200176
17 200019
18 199914
19 199215
20 198913

About Monica Galliano

Monica Galliano is a scholar working on Hematology, Molecular Biology and Cell Biology, having authored 103 papers that have together received 3.1k indexed citations. Recurring topics across this work include Protein Interaction Studies and Fluorescence Analysis (62 papers), Hemoglobin structure and function (17 papers), Monoclonal and Polyclonal Antibodies Research (16 papers), Mass Spectrometry Techniques and Applications (15 papers), Protein purification and stability (15 papers), Erythrocyte Function and Pathophysiology (13 papers), Drug Transport and Resistance Mechanisms (13 papers) and Glycosylation and Glycoproteins Research (11 papers). The work is most often cited by research in Molecular Biology (2.3k citations), Cell Biology (466 citations) and Spectroscopy (432 citations). Monica Galliano has collaborated with scholars based in Italy, Denmark and United States. Frequent co-authors include Lorenzo Minchiotti, Mauro Fasano, Stefania Notari, Stephen Curry, Enzo Terreno, Pasquale Narciso, Paolo Ascenzi, Gabriella Fanali, Ulrich Kragh‐Hansen and Monica Campagnoli. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Biochemistry.

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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