Simone Fulle

2.2k citations
30 papers · 1.5k · 1 hit paper · h-index 17

Impact in

Papers in

Simone Fulle

29 papers receiving 1.5k citations

Simone Fulle's Hit Papers

Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition 2017 · 500 citations
5000+3+6Years since publication100200300400500

Peers

Simone Fulle
Comparison fields: 5 of 122
  • Computational Theory and Mathematics 607
  • Molecular Biology 872
  • Materials Chemistry 334
  • Pharmacology 99
  • Virology 21
Replace David J. Huggins with:
David J. Huggins United States
Rafaël Najmanovich Canada
José M. Duarte United States
Daniel K. Gehlhaar United States
Inbal Halperin United States
Pieter F. W. Stouten United States
Donald Petrey United States
R.H.A. Folmer Sweden
José S. Duca United States
Nurcan Tunçbağ Türkiye
Simone Fulle relative to David J. Huggins United States David J. Huggins's profile →
Citations per field
00.5×1.5×
David J. Huggins · 1×
Citations per year

Countries citing papers authored by Simone Fulle

Since Specialization
Citations

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

Fields of papers citing papers by Simone Fulle

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition
Hit paper breakdown →
2017500
2 2017237
3 201688
4 202184
5 200978
6 201760
7 200957
8 201246
9 201638
10 200836
11 201428
12 201427
13 201726
14 201025
15 201324
16 200921
17 201318
18 201615
19 201715
20 201313

About Simone Fulle

Simone Fulle is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Public Health, Environmental and Occupational Health and Genetics, having authored 30 papers that have together received 1.5k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (12 papers), Protein Structure and Dynamics (11 papers), RNA and protein synthesis mechanisms (9 papers), Enzyme Structure and Function (5 papers), Machine Learning in Materials Science (3 papers), Malaria Research and Control (3 papers), DNA and Nucleic Acid Chemistry (3 papers) and Bacterial Genetics and Biotechnology (3 papers). The work is most often cited by research in Computational Theory and Mathematics (607 citations), Molecular Biology (872 citations), Materials Chemistry (334 citations), Pharmacology (99 citations) and Virology (21 citations). Simone Fulle has collaborated with scholars based in Germany, United Kingdom and Latvia. Frequent co-authors include Sabrina Jaeger-Honz, Holger Gohlke, Sameh Eid, Friedrich Rippmann, Andrea Volkamer, Benjamin Merget, Paul W. Finn, Michael J. Blackman, Jean-Paul Ebejer and Aigars Jirgensons. Their work appears in journals such as Journal of Chemical Information and Modeling, Journal of Medicinal Chemistry, Molecular Neurodegeneration, The Journal of Physical Chemistry B and Journal of Molecular Graphics and Modelling.

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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