Lucio Comai

4.4k total citations
67 papers, 3.7k citations indexed

About

Lucio Comai is a scholar working on Molecular Biology, Plant Science and Cellular and Molecular Neuroscience. According to data from OpenAlex, Lucio Comai has authored 67 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Molecular Biology, 12 papers in Plant Science and 11 papers in Cellular and Molecular Neuroscience. Recurrent topics in Lucio Comai's work include RNA Research and Splicing (19 papers), DNA Repair Mechanisms (17 papers) and Genomics and Chromatin Dynamics (12 papers). Lucio Comai is often cited by papers focused on RNA Research and Splicing (19 papers), DNA Repair Mechanisms (17 papers) and Genomics and Chromatin Dynamics (12 papers). Lucio Comai collaborates with scholars based in United States, United Kingdom and Peru. Lucio Comai's co-authors include Baomin Li, Robert Tjian, Sita Reddy, Weiguo Zhai, Naoko Tanese, John J. Harada, Warunee Dansithong, Sharan Paul, Joost C.B.M. Zomerdijk and Holger Beckmann and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Lucio Comai

65 papers receiving 3.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lucio Comai United States 33 3.1k 476 400 367 275 67 3.7k
Toshiki Itoh Japan 32 2.9k 0.9× 148 0.3× 205 0.5× 325 0.9× 311 1.1× 75 4.0k
Sophie G. Martin Switzerland 33 3.4k 1.1× 538 1.1× 215 0.5× 153 0.4× 230 0.8× 85 4.0k
Luciana Dente Italy 30 2.5k 0.8× 261 0.5× 299 0.7× 267 0.7× 643 2.3× 57 3.5k
Kazuma Tanaka Japan 42 4.4k 1.4× 834 1.8× 226 0.6× 325 0.9× 216 0.8× 110 5.7k
Yegor Vassetzky France 35 2.7k 0.9× 229 0.5× 94 0.2× 456 1.2× 404 1.5× 160 3.4k
Dae In Kim United States 15 2.7k 0.9× 229 0.5× 169 0.4× 181 0.5× 263 1.0× 29 3.9k
Giuseppe Biamonti Italy 47 5.5k 1.8× 457 1.0× 105 0.3× 525 1.4× 445 1.6× 114 6.3k
S P Adams United States 26 2.0k 0.7× 124 0.3× 236 0.6× 348 0.9× 233 0.8× 37 3.5k
Andrew C.G. Porter United Kingdom 32 2.8k 0.9× 265 0.6× 143 0.4× 999 2.7× 366 1.3× 83 3.6k
Naoyuki Kataoka Japan 28 4.3k 1.4× 160 0.3× 117 0.3× 149 0.4× 255 0.9× 65 4.8k

Countries citing papers authored by Lucio Comai

Since Specialization
Citations

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

Fields of papers citing papers by Lucio Comai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lucio Comai

This figure shows the co-authorship network connecting the top 25 collaborators of Lucio Comai. A scholar is included among the top collaborators of Lucio Comai 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 Lucio Comai. Lucio Comai 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.
Rao, Youliang, Chao Qin, Tingyu Wang, et al.. (2025). Targeting CTP synthetase 1 to restore interferon induction and impede nucleotide synthesis in SARS-CoV-2 infection. mBio. 16(6). e0064925–e0064925.
2.
Liu, Zhewei, Siyang Chen, Jill Henley, et al.. (2023). Potent NKT cell ligands overcome SARS-CoV-2 immune evasion to mitigate viral pathogenesis in mouse models. PLoS Pathogens. 19(3). e1011240–e1011240. 9 indexed citations
3.
Maria, Naomi S. Sta, Jongkyu Choi, Xiaodan Liu, et al.. (2021). Mbnl1 and Mbnl2 regulate brain structural integrity in mice. Communications Biology. 4(1). 1342–1342. 11 indexed citations
4.
Iglesias‐Pedraz, Juan Manuel, et al.. (2020). WRN modulates translation by influencing nuclear mRNA export in HeLa cancer cells. BMC Molecular and Cell Biology. 21(1). 71–71. 8 indexed citations
5.
Choi, Jongkyu, Warunee Dansithong, Walid Abdallah, et al.. (2016). Muscleblind-like 3 deficit results in a spectrum of age-associated pathologies observed in myotonic dystrophy. Scientific Reports. 6(1). 30999–30999. 22 indexed citations
6.
Choi, Jongkyu, Sun Young Park, Kenneth P. Roos, et al.. (2015). Loss of muscleblind-like 1 results in cardiac pathology and persistence of embryonic splice isoforms. Scientific Reports. 5(1). 9042–9042. 62 indexed citations
7.
Li, Baomin, Juan Manuel Iglesias‐Pedraz, Fei Yin, et al.. (2013). Downregulation of the Werner syndrome protein induces a metabolic shift that compromises redox homeostasis and limits proliferation of cancer cells. Aging Cell. 13(2). 367–378. 25 indexed citations
8.
Li, Baomin, et al.. (2009). Altered Nuclear Functions in Progeroid Syndromes: a Paradigm for Aging Research. The Scientific World JOURNAL. 9. 1449–1462. 9 indexed citations
9.
Sivasubramaniam, Sudhakar, et al.. (2008). Perturbation of wild‐type lamin A metabolism results in a progeroid phenotype. Aging Cell. 7(3). 355–367. 40 indexed citations
10.
Ficarro, Scott B., Mark H. Hoofnagle, Jeffrey Shabanowitz, et al.. (2006). Mass spectrometric identification of phosphorylation sites of rRNA transcription factor upstream binding factor. American Journal of Physiology-Cell Physiology. 292(5). C1617–C1624. 9 indexed citations
11.
Navarro, Sonia, et al.. (2006). CK2-mediated stimulation of Pol I transcription by stabilization of UBF–SL1 interaction. Nucleic Acids Research. 34(17). 4752–4766. 36 indexed citations
12.
Paul, Sharan, Warunee Dansithong, Dongho Kim, et al.. (2006). Interaction of musleblind, CUG‐BP1 and hnRNP H proteins in DM1‐associated aberrant IR splicing. The EMBO Journal. 25(18). 4271–4283. 128 indexed citations
13.
Sheng, Zhi, et al.. (2005). Direct Regulation of rRNA Transcription by Fibroblast Growth Factor 2. Molecular and Cellular Biology. 25(21). 9419–9426. 38 indexed citations
14.
Dansithong, Warunee, Sharan Paul, Lucio Comai, & Sita Reddy. (2004). MBNL1 Is the Primary Determinant of Focus Formation and Aberrant Insulin Receptor Splicing in DM1. Journal of Biological Chemistry. 280(7). 5773–5780. 162 indexed citations
15.
Comai, Lucio. (2004). Mechanism of RNA Polymerase I Transcription. Advances in protein chemistry. 67. 123–155. 22 indexed citations
16.
Li, Baomin & Lucio Comai. (2001). Requirements for the Nucleolytic Processing of DNA Ends by the Werner Syndrome Protein-Ku70/80 Complex. Journal of Biological Chemistry. 276(13). 9896–9902. 92 indexed citations
17.
18.
Comai, Lucio, et al.. (1997). SV40 large T antigen binds to the TBP-TAF(I) complex SL1 and coactivates ribosomal RNA transcription.. Genes & Development. 11(12). 1605–1617. 53 indexed citations
19.
Roussel, Pascal, Claire André, Lucio Comai, & D. Hernandez‐Verdun. (1996). The rDNA transcription machinery is assembled during mitosis in active NORs and absent in inactive NORs.. The Journal of Cell Biology. 133(2). 235–246. 216 indexed citations
20.
Comai, Lucio, et al.. (1986). Mechanism of action of herbicides and their molecular manipulation.. Europe PMC (PubMed Central). 3. 166–195. 11 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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