Massimo Sammito

8.8k citations
32 papers · 612 · h-index 15

Impact in

Papers in

    • Enzyme Structure and Function 24
    • Machine Learning in Materials Science 2
    • Protein Structure and Dynamics 19
    • Microbial Metabolic Engineering and Bioproduction 3
    • RNA and protein synthesis mechanisms 3
    • Glycosylation and Glycoproteins Research 2
    • DNA and Nucleic Acid Chemistry 2

Massimo Sammito

29 papers receiving 611 citations

Peers

Massimo Sammito
Comparison fields: 5 of 73
  • Structural Biology 17
  • Materials Chemistry 371
  • Molecular Biology 485
  • Virology 20
  • Microbiology 26
Replace Claudia Millán with:
Claudia Millán Spain
Alejandro De María Antolinos France
Karen Manalastas-Cantos Germany
S. Ohlsson France
Oleg Kovalevskiy United Kingdom
Lisa J. Keefe United States
Sébastien Violot France
Phil Bradley United States
Lawrence Kahan United States
С.В. Никонов Russia
Massimo Sammito relative to Claudia Millán Spain Claudia Millán's profile →
Citations per field
00.5×1.5×
Claudia Millán · 1×
Citations per year

Countries citing papers authored by Massimo Sammito

Since Specialization
Citations

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

Fields of papers citing papers by Massimo Sammito

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201355
2 202148
3 201548
4 201947
5 202146
6 201246
7 201442
8 201439
9 201835
10 201833
11 201827
12 201923
13 201618
14 201816
15 201416
16 201514
17 202013
18 202210
19 202010
20 20208

About Massimo Sammito

Massimo Sammito is a scholar working on Materials Chemistry, Molecular Biology, Spectroscopy, Inorganic Chemistry and Discrete Mathematics and Combinatorics, having authored 32 papers that have together received 612 indexed citations. Recurring topics across this work include Enzyme Structure and Function (24 papers), Protein Structure and Dynamics (19 papers), Microbial Metabolic Engineering and Bioproduction (3 papers), RNA and protein synthesis mechanisms (3 papers), Machine Learning in Materials Science (2 papers), Glycosylation and Glycoproteins Research (2 papers), DNA and Nucleic Acid Chemistry (2 papers) and Mass Spectrometry Techniques and Applications (2 papers). The work is most often cited by research in Structural Biology (17 citations), Materials Chemistry (371 citations), Molecular Biology (485 citations), Virology (20 citations) and Microbiology (26 citations). Massimo Sammito has collaborated with scholars based in Spain, United Kingdom and Germany. Frequent co-authors include Isabel Usón, Claudia Millán, Randy J. Read, K. Meindl, Tristan I. Croll, Airlie J. McCoy, Andriy Kryshtafovych, Iñaki M. de Ilarduya, George M. Sheldrick and Rafael J. Borges. Their work appears in journals such as Acta Crystallographica Section D Structural Biology, Acta Crystallographica Section A Foundations and Advances, Proteins Structure Function and Bioinformatics, IUCrJ and Nature Methods.

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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