Marco Punta

25.1k total citations · 5 hit papers
59 papers, 15.3k citations indexed

About

Marco Punta is a scholar working on Molecular Biology, Materials Chemistry and Spectroscopy. According to data from OpenAlex, Marco Punta has authored 59 papers receiving a total of 15.3k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Molecular Biology, 13 papers in Materials Chemistry and 8 papers in Spectroscopy. Recurrent topics in Marco Punta's work include Protein Structure and Dynamics (25 papers), Machine Learning in Bioinformatics (23 papers) and RNA and protein synthesis mechanisms (16 papers). Marco Punta is often cited by papers focused on Protein Structure and Dynamics (25 papers), Machine Learning in Bioinformatics (23 papers) and RNA and protein synthesis mechanisms (16 papers). Marco Punta collaborates with scholars based in United States, United Kingdom and Italy. Marco Punta's co-authors include Alex Bateman, Jaina Mistry, ROBERT FINN, Sean R. Eddy, Ruth Y. Eberhardt, John Tate, Penelope Coggill, Andreas Heger, Jody Clements and Erik L. L. Sonnhammer and has published in prestigious journals such as Nature, Nucleic Acids Research and Nature Communications.

In The Last Decade

Marco Punta

57 papers receiving 15.1k citations

Hit Papers

Pfam: the protein families database 2011 2026 2016 2021 2013 2015 2011 2013 2014 1000 2.0k 3.0k 4.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marco Punta United States 29 10.5k 4.0k 2.1k 1.8k 845 59 15.3k
Ruth Y. Eberhardt United Kingdom 17 9.3k 0.9× 3.9k 1.0× 2.0k 1.0× 1.7k 1.0× 449 0.5× 28 13.7k
Jody Clements United States 20 11.0k 1.0× 4.3k 1.1× 2.1k 1.0× 1.9k 1.1× 467 0.6× 25 16.2k
Andreas Heger United Kingdom 34 10.7k 1.0× 3.3k 0.8× 1.7k 0.8× 2.2k 1.3× 569 0.7× 55 15.9k
Simon Potter United Kingdom 13 8.4k 0.8× 3.6k 0.9× 1.9k 0.9× 1.4k 0.8× 485 0.6× 19 13.0k
Silvio C. E. Tosatto Italy 48 10.9k 1.0× 2.7k 0.7× 1.3k 0.6× 1.3k 0.8× 1.4k 1.7× 182 14.8k
John Tate United Kingdom 19 14.0k 1.3× 5.1k 1.3× 2.8k 1.3× 2.5k 1.4× 723 0.9× 23 20.2k
Thomas Dandekar Germany 61 8.6k 0.8× 1.8k 0.4× 1.8k 0.9× 1.3k 0.8× 493 0.6× 369 14.8k
Gustavo A Salazar United Kingdom 11 7.7k 0.7× 3.7k 0.9× 1.7k 0.8× 1.3k 0.7× 383 0.5× 17 11.5k
Matloob Qureshi United Kingdom 6 7.5k 0.7× 3.6k 0.9× 1.7k 0.8× 1.3k 0.7× 377 0.4× 6 11.2k
Michael Remmert Germany 11 9.1k 0.9× 2.2k 0.5× 1.6k 0.8× 1.7k 1.0× 957 1.1× 14 14.0k

Countries citing papers authored by Marco Punta

Since Specialization
Citations

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

Fields of papers citing papers by Marco Punta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marco Punta

This figure shows the co-authorship network connecting the top 25 collaborators of Marco Punta. A scholar is included among the top collaborators of Marco Punta 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 Marco Punta. Marco Punta 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.
Laio, Alessandro, et al.. (2025). Unsupervised Domain Classification of AlphaFold2-Predicted Protein Structures. 3(2). 1 indexed citations
2.
García‐Mulero, Sandra, Marco Punta, Stefano Lise, et al.. (2023). Driver mutations in GNAQ and GNA11 genes as potential targets for precision immunotherapy in uveal melanoma patients. OncoImmunology. 12(1). 2261278–2261278. 5 indexed citations
3.
Arbore, Giuseppina, Luca Albarello, Gabriele Bucci, et al.. (2023). Preexisting Immunity Drives the Response to Neoadjuvant Chemotherapy in Esophageal Adenocarcinoma. Cancer Research. 83(17). 2873–2888. 10 indexed citations
4.
Bateman, Alex, et al.. (2022). DPCfam: Unsupervised protein family classification by Density Peak Clustering of large sequence datasets. PLoS Computational Biology. 18(10). e1010610–e1010610. 7 indexed citations
5.
Pettitt, Stephen J., Jessica Frankum, Marco Punta, et al.. (2020). Clinical BRCA1/2 Reversion Analysis Identifies Hotspot Mutations and Predicted Neoantigens Associated with Therapy Resistance. Cancer Discovery. 10(10). 1475–1488. 114 indexed citations
6.
Loga, Katharina von, Andrew Woolston, Marco Punta, et al.. (2020). Extreme intratumour heterogeneity and driver evolution in mismatch repair deficient gastro-oesophageal cancer. Nature Communications. 11(1). 139–139. 43 indexed citations
7.
Punta, Marco, Victoria A. Jennings, Alan Melcher, & Stefano Lise. (2020). The Immunogenic Potential of Recurrent Cancer Drug Resistance Mutations: An In Silico Study. Frontiers in Immunology. 11. 524968–524968. 7 indexed citations
8.
Liu, Qun, Oliver B. Clarke, Meagan Belcher Dufrisne, et al.. (2018). Structure-based analysis of CysZ-mediated cellular uptake of sulfate. eLife. 7. 27 indexed citations
9.
FINN, ROBERT, Penelope Coggill, Ruth Y. Eberhardt, et al.. (2015). The Pfam protein families database: towards a more sustainable future. Nucleic Acids Research. 44(D1). D279–D285. 4051 indexed citations breakdown →
11.
Kumar, Abhinav, Marco Punta, Herbert L. Axelrod, et al.. (2014). Crystal structures of three representatives of a new Pfam family PF14869 (DUF4488) suggest they function in sugar binding/uptake. Protein Science. 23(10). 1380–1391. 2 indexed citations
12.
Mistry, Jaina, Penny Coggill, Ruth Y. Eberhardt, et al.. (2013). The challenge of increasing Pfam coverage of the human proteome. Database. 2013. bat023–bat023. 23 indexed citations
13.
FINN, ROBERT, Alex Bateman, Jody Clements, et al.. (2013). Pfam: the protein families database. Nucleic Acids Research. 42(D1). D222–D230. 4740 indexed citations breakdown →
14.
Mistry, Jaina, Edda Kloppmann, Burkhard Rost, & Marco Punta. (2013). An estimated 5% of new protein structures solved today represent a new Pfam family. Acta Crystallographica Section D Biological Crystallography. 69(11). 2186–2193. 11 indexed citations
15.
Wu, Yibing, Marco Punta, Rong Xiao, et al.. (2012). NMR Structure of Lipoprotein YxeF from Bacillus subtilis Reveals a Calycin Fold and Distant Homology with the Lipocalin Blc from Escherichia coli. PLoS ONE. 7(6). e37404–e37404. 6 indexed citations
16.
Schlessinger, Avner, et al.. (2011). Protein disorder—a breakthrough invention of evolution?. Current Opinion in Structural Biology. 21(3). 412–418. 115 indexed citations
17.
Shi, Wuxian, Marco Punta, Jen Bohon, et al.. (2011). Characterization of metalloproteins by high-throughput X-ray absorption spectroscopy. Genome Research. 21(6). 898–907. 36 indexed citations
18.
Kann, Maricel G., Yanay Ofran, Marco Punta, & Predrag Radivojac. (2007). PROTEIN INTERACTIONS AND DISEASE. 29 indexed citations
19.
Punta, Marco & Burkhard Rost. (2005). PROFcon: novel prediction of long-range contacts. Computer applications in the biosciences. 21(13). 2960–2968. 110 indexed citations
20.
Ofran, Yanay, Marco Punta, Reinhard Schneider, & Burkhard Rost. (2005). Beyond annotation transfer by homology: novel protein-function prediction methods to assist drug discovery. Drug Discovery Today. 10(21). 1475–1482. 63 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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