Sheref S. Mansy

5.0k total citations · 1 hit paper
77 papers, 3.6k citations indexed

About

Sheref S. Mansy is a scholar working on Molecular Biology, Astronomy and Astrophysics and Cellular and Molecular Neuroscience. According to data from OpenAlex, Sheref S. Mansy has authored 77 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Molecular Biology, 30 papers in Astronomy and Astrophysics and 20 papers in Cellular and Molecular Neuroscience. Recurrent topics in Sheref S. Mansy's work include Origins and Evolution of Life (30 papers), Metalloenzymes and iron-sulfur proteins (20 papers) and Photoreceptor and optogenetics research (19 papers). Sheref S. Mansy is often cited by papers focused on Origins and Evolution of Life (30 papers), Metalloenzymes and iron-sulfur proteins (20 papers) and Photoreceptor and optogenetics research (19 papers). Sheref S. Mansy collaborates with scholars based in Italy, United States and Canada. Sheref S. Mansy's co-authors include Jack W. Szostak, J. A. Cowan, Mathangi Krishnamurthy, Douglas A. Treco, Jason Schrum, Sylvia Tobé, Laura Martini, Michele Forlin, Noël Yeh Martín and G. González and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Sheref S. Mansy

74 papers receiving 3.6k citations

Hit Papers

Template-directed synthesis of a genetic polymer in a mod... 2008 2026 2014 2020 2008 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Sheref S. Mansy Italy 33 2.5k 1.0k 809 582 540 77 3.6k
Pasquale Stano Italy 36 3.5k 1.4× 1.1k 1.1× 966 1.2× 48 0.1× 1.1k 2.0× 141 4.8k
Kentaro Suzuki Japan 26 799 0.3× 259 0.2× 262 0.3× 186 0.3× 544 1.0× 112 2.5k
Gonen Ashkenasy Israel 35 2.0k 0.8× 1.1k 1.0× 878 1.1× 66 0.1× 505 0.9× 80 3.7k
Nediljko Budiša Germany 46 5.9k 2.3× 81 0.1× 319 0.4× 71 0.1× 232 0.4× 220 7.3k
Andrés de la Escosura Spain 28 907 0.4× 592 0.6× 326 0.4× 100 0.2× 533 1.0× 55 2.8k
Jean‐Louis Rigaud France 36 3.5k 1.4× 38 0.0× 652 0.8× 183 0.3× 388 0.7× 53 4.3k
Fabio Mavelli Italy 24 1.3k 0.5× 465 0.4× 456 0.6× 57 0.1× 378 0.7× 68 2.0k
Matthew Levy United States 32 3.8k 1.5× 546 0.5× 291 0.4× 21 0.0× 811 1.5× 70 4.6k
Paula J. Booth United Kingdom 45 5.0k 2.0× 39 0.0× 1.1k 1.4× 88 0.2× 533 1.0× 118 6.2k
Chikashi Nakamura Japan 31 1.4k 0.6× 54 0.1× 402 0.5× 156 0.3× 1.0k 1.9× 152 3.2k

Countries citing papers authored by Sheref S. Mansy

Since Specialization
Citations

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

Fields of papers citing papers by Sheref S. Mansy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sheref S. Mansy. 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 Sheref S. Mansy. The network helps show where Sheref S. Mansy may publish in the future.

Co-authorship network of co-authors of Sheref S. Mansy

This figure shows the co-authorship network connecting the top 25 collaborators of Sheref S. Mansy. A scholar is included among the top collaborators of Sheref S. Mansy 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 Sheref S. Mansy. Sheref S. Mansy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Rossetto, Daniele, et al.. (2024). Peptide Mimics of the Cysteine‐Rich Regions of HapX and SreA Bind a [2Fe‐2S] Cluster In Vitro. Advanced Biology. 8(5). e2300545–e2300545. 4 indexed citations
3.
Kaur, Harpreet, et al.. (2024). A Magnesium Binding Site And The Anomeric Effect Regulate The Abiotic Redox Chemistry Of Nicotinamide Nucleotides. Chemistry - A European Journal. 30(35). e202400411–e202400411. 4 indexed citations
4.
Walton, Craig R., et al.. (2024). Prebiotic Environmental Conditions Impact the Type of Iron‐Sulfur Cluster Formed. ChemSystemsChem. 7(1). 2 indexed citations
5.
Toparlak, Ö. Duhan, Megha Karki, Yanfeng Xing, et al.. (2023). Cyclophospholipids Enable a Protocellular Life Cycle. ACS Nano. 17(23). 23772–23783. 8 indexed citations
6.
Rossetto, Daniele, et al.. (2022). Histidine Ligated Iron‐Sulfur Peptides. ChemBioChem. 23(14). e202200202–e202200202. 9 indexed citations
7.
Peng, Huan, Daniele Rossetto, Sheref S. Mansy, et al.. (2022). Treatment of Wound Infections in a Mouse Model Using Zn 2+ -Releasing Phage Bound to Gold Nanorods. ACS Nano. 16(3). 4756–4774. 83 indexed citations
8.
Rossetto, Daniele, et al.. (2022). Prebiotic Environments with Mg2+ and Thiophilic Metal Ions Increase the Thermal Stability of Cysteine and Non-cysteine Peptides. ACS Earth and Space Chemistry. 6(5). 1221–1226. 6 indexed citations
9.
Mansy, Sheref S., et al.. (2021). Spectral decomposition of iron-sulfur clusters. Analytical Biochemistry. 629. 114269–114269. 6 indexed citations
10.
Ha, Michelle, Shane Pawsey, Jochem Struppe, et al.. (2021). Racing toward Fast and Effective 17O Isotopic Labeling and Nuclear Magnetic Resonance Spectroscopy of N-Formyl-MLF-OH and Associated Building Blocks. The Journal of Physical Chemistry B. 125(43). 11916–11926. 6 indexed citations
11.
Basak, Shibaji, et al.. (2021). Protometabolic Reduction of NAD+ with α-Keto Acids. SHILAP Revista de lepidopterología. 1(4). 371–374. 18 indexed citations
12.
Rossetto, Daniele, et al.. (2020). Cell‐Free Synthesis of Dopamine and Serotonin in Two Steps with Purified Enzymes. Advanced Biosystems. 4(11). e2000118–e2000118. 7 indexed citations
13.
Toparlak, Ö. Duhan, et al.. (2019). Cyclophospholipids Increase Protocellular Stability to Metal Ions. Small. 16(27). e1903381–e1903381. 32 indexed citations
14.
Toparlak, Ö. Duhan & Sheref S. Mansy. (2018). Progress in synthesizing protocells. Experimental Biology and Medicine. 244(4). 304–313. 44 indexed citations
15.
Bonfio, Claudia, et al.. (2018). Prebiotic iron–sulfur peptide catalysts generate a pH gradient across model membranes of late protocells. Nature Catalysis. 1(8). 616–623. 78 indexed citations
16.
Chizzolini, Fabio, et al.. (2017). Cell-Free Translation Is More Variable than Transcription. ACS Synthetic Biology. 6(4). 638–647. 36 indexed citations
17.
Bonfio, Claudia, Simone Scintilla, David J. Evans, et al.. (2017). UV-light-driven prebiotic synthesis of iron–sulfur clusters. Nature Chemistry. 9(12). 1229–1234. 120 indexed citations
18.
Scintilla, Simone, Claudia Bonfio, Luca Belmonte, et al.. (2016). Duplications of an iron–sulphur tripeptide leads to the formation of a protoferredoxin. Chemical Communications. 52(92). 13456–13459. 36 indexed citations
19.
Martín, Noël Yeh, et al.. (2016). Communicating artificial cells. Current Opinion in Chemical Biology. 34. 53–61. 73 indexed citations
20.
Belmonte, Luca, Daniele Rossetto, Michele Forlin, et al.. (2016). Cysteine containing dipeptides show a metal specificity that matches the composition of seawater. Physical Chemistry Chemical Physics. 18(30). 20104–20108. 15 indexed citations

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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