Danny Incarnato

5.1k total citations · 1 hit paper
61 papers, 3.2k citations indexed

About

Danny Incarnato is a scholar working on Molecular Biology, Cancer Research and Cellular and Molecular Neuroscience. According to data from OpenAlex, Danny Incarnato has authored 61 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Molecular Biology, 10 papers in Cancer Research and 3 papers in Cellular and Molecular Neuroscience. Recurrent topics in Danny Incarnato's work include RNA modifications and cancer (29 papers), RNA and protein synthesis mechanisms (28 papers) and RNA Research and Splicing (20 papers). Danny Incarnato is often cited by papers focused on RNA modifications and cancer (29 papers), RNA and protein synthesis mechanisms (28 papers) and RNA Research and Splicing (20 papers). Danny Incarnato collaborates with scholars based in Italy, Netherlands and United States. Danny Incarnato's co-authors include Salvatore Oliviero, Francesco Neri, Caterina Parlato, Francesca Anselmi, Anna Křepelová, Stefania Rapelli, Mara Maldotti, Giulia Basile, Edoardo Morandi and Robert C. Spitale and has published in prestigious journals such as Nature, Cell and Nucleic Acids Research.

In The Last Decade

Danny Incarnato

58 papers receiving 3.2k citations

Hit Papers

Intragenic DNA methylation prevents spurious transcriptio... 2017 2026 2020 2023 2017 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Danny Incarnato Italy 27 2.8k 673 276 155 155 61 3.2k
Naoyuki Kataoka Japan 28 4.3k 1.5× 382 0.6× 255 0.9× 149 1.0× 204 1.3× 65 4.8k
Tien Hsu United States 31 2.0k 0.7× 414 0.6× 420 1.5× 284 1.8× 281 1.8× 72 2.7k
Isabelle Behm‐Ansmant France 24 3.9k 1.4× 1.2k 1.8× 176 0.6× 122 0.8× 187 1.2× 41 4.2k
Keith A. Spriggs United Kingdom 22 2.5k 0.9× 470 0.7× 149 0.5× 242 1.6× 194 1.3× 36 3.0k
Aleyde Van Eynde Belgium 27 3.3k 1.2× 472 0.7× 397 1.4× 317 2.0× 212 1.4× 52 3.9k
Bing Zhou China 28 2.0k 0.7× 463 0.7× 160 0.6× 210 1.4× 200 1.3× 85 2.9k
Haidi Zhang China 15 1.8k 0.6× 908 1.3× 159 0.6× 93 0.6× 243 1.6× 34 2.3k
Thomas F. Duchaîne Canada 28 3.0k 1.1× 1.2k 1.8× 167 0.6× 97 0.6× 184 1.2× 52 3.6k
Shawn M. Lyons United States 23 2.8k 1.0× 558 0.8× 69 0.3× 60 0.4× 153 1.0× 44 3.1k
Joshua Babiarz United States 23 3.2k 1.1× 2.0k 2.9× 427 1.5× 174 1.1× 323 2.1× 38 4.3k

Countries citing papers authored by Danny Incarnato

Since Specialization
Citations

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

Fields of papers citing papers by Danny Incarnato

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Danny Incarnato

This figure shows the co-authorship network connecting the top 25 collaborators of Danny Incarnato. A scholar is included among the top collaborators of Danny Incarnato 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 Danny Incarnato. Danny Incarnato 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
2.
Karollus, Alexander, et al.. (2025). Nucleotide dependency analysis of genomic language models detects functional elements. Nature Genetics. 57(10). 2589–2602.
3.
Incarnato, Danny, et al.. (2025). Site‐Selective Ligand Selection by Mutational Profiling for Covalent RNA Targeting. Angewandte Chemie International Edition. 65(6). e17243–e17243.
4.
Incarnato, Danny, et al.. (2025). Low butyrate concentrations exert anti-inflammatory and high concentrations exert pro-inflammatory effects on macrophages. The Journal of Nutritional Biochemistry. 144. 109962–109962. 3 indexed citations
5.
Bonilla, Steve, Alisha Jones, & Danny Incarnato. (2024). Structural and biophysical dissection of RNA conformational ensembles. Current Opinion in Structural Biology. 88. 102908–102908. 4 indexed citations
6.
Calabrese, David, Liang Xiao, Ronald J. Holewinski, et al.. (2023). Investigating the NRAS 5′ UTR as a target for small molecules. Cell chemical biology. 30(6). 643–657.e8. 21 indexed citations
7.
Proserpio, Valentina, Stefania Rapelli, Mara Maldotti, et al.. (2023). DNMT3B supports meso-endoderm differentiation from mouse embryonic stem cells. Nature Communications. 14(1). 11 indexed citations
8.
Chiariello, Andrea M., Andrea Esposito, Pietro Zoppoli, et al.. (2022). Hmga2 protein loss alters nuclear envelope and 3D chromatin structure. BMC Biology. 20(1). 171–171. 10 indexed citations
9.
Maldotti, Mara, Francesca Anselmi, Ivan Molineris, et al.. (2022). The acetyltransferase p300 is recruited in trans to multiple enhancer sites by lncSmad7. Nucleic Acids Research. 50(5). 2587–2602. 13 indexed citations
10.
Spitale, Robert C. & Danny Incarnato. (2022). Probing the dynamic RNA structurome and its functions. Nature Reviews Genetics. 24(3). 178–196. 112 indexed citations
11.
Avalle, Lidia, Emanuele Monteleone, Aurora Savino, et al.. (2022). STAT3 induces breast cancer growth via ANGPTL4, MMP13 and STC1 secretion by cancer associated fibroblasts. Oncogene. 41(10). 1456–1467. 62 indexed citations
12.
Rhodes, Curran A., Desta Doro Bume, Colleen M. Connelly, et al.. (2021). A chemical probe based on the PreQ1 metabolite enables transcriptome-wide mapping of binding sites. Nature Communications. 12(1). 5856–5856. 35 indexed citations
13.
Morandi, Edoardo, et al.. (2021). Genome-scale deconvolution of RNA structure ensembles. Nature Methods. 18(3). 249–252. 82 indexed citations
14.
Marinus, Tycho, Adam B. Fessler, Craig A. Ogle, & Danny Incarnato. (2020). A novel SHAPE reagent enables the analysis of RNA structure in living cells with unprecedented accuracy. Nucleic Acids Research. 49(6). e34–e34. 61 indexed citations
15.
Nithin, Chandran, Almudena Ponce-Salvatierra, Pritha Ghosh, et al.. (2020). Genome-wide mapping of SARS-CoV-2 RNA structures identifies therapeutically-relevant elements. Nucleic Acids Research. 48(22). 12436–12452. 189 indexed citations
16.
Pellegrini, Marco, Danny Incarnato, Mara Maldotti, et al.. (2020). The transcriptional regulator ZNF398 mediates pluripotency and epithelial character downstream of TGF-beta in human PSCs. Nature Communications. 11(1). 2364–2364. 24 indexed citations
17.
Managò, Antonella, Valentina Audrito, Francesca Mazzola, et al.. (2019). Extracellular nicotinate phosphoribosyltransferase binds Toll like receptor 4 and mediates inflammation. Nature Communications. 10(1). 4116–4116. 55 indexed citations
18.
Morandi, Edoardo, Matteo Cereda, Danny Incarnato, et al.. (2019). HaTSPiL: A modular pipeline for high-throughput sequencing data analysis. PLoS ONE. 14(10). e0222512–e0222512. 3 indexed citations
19.
Neri, Francesco, Danny Incarnato, Anna Křepelová, Caterina Parlato, & Salvatore Oliviero. (2016). Methylation-assisted bisulfite sequencing to simultaneously map 5fC and 5caC on a genome-wide scale for DNA demethylation analysis. Nature Protocols. 11(7). 1191–1205. 28 indexed citations
20.
Diamanti, Daniela, et al.. (2013). Whole gene expression profile in blood reveals multiple pathways deregulation in R6/2 mouse model. Biomarker Research. 1(1). 28–28. 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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