Gianluca Pegoraro

4.0k total citations · 1 hit paper
63 papers, 2.6k citations indexed

About

Gianluca Pegoraro is a scholar working on Molecular Biology, Genetics and Biophysics. According to data from OpenAlex, Gianluca Pegoraro has authored 63 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Molecular Biology, 12 papers in Genetics and 10 papers in Biophysics. Recurrent topics in Gianluca Pegoraro's work include Genomics and Chromatin Dynamics (28 papers), RNA Research and Splicing (20 papers) and Cell Image Analysis Techniques (9 papers). Gianluca Pegoraro is often cited by papers focused on Genomics and Chromatin Dynamics (28 papers), RNA Research and Splicing (20 papers) and Cell Image Analysis Techniques (9 papers). Gianluca Pegoraro collaborates with scholars based in United States, Italy and Japan. Gianluca Pegoraro's co-authors include Tom Misteli, Sigal Shachar, Elizabeth H. Finn, Leonid A. Mirny, Anne-Laure Valton, Nard Kubben, Hugo B. Brandão, Job Dekker, Marlies E. Oomen and Sina Bavari and has published in prestigious journals such as Nature, Cell and Nucleic Acids Research.

In The Last Decade

Gianluca Pegoraro

60 papers receiving 2.6k citations

Hit Papers

Protection against filovirus diseases by a novel broad-sp... 2014 2026 2018 2022 2014 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Protection against filovirus diseases by a novel broad-spectrum nucleoside analogue BCX4430
    2014 461 citations Lián Dŏng, Gianluca Pegoraro et al. profile →

Peers

Gianluca Pegoraro
Christopher T. Eggers United States
Colin Logie Netherlands
Braeden L. Butler United States
Bastien Mangeat Switzerland
Yingfang Liu China
Vibor Laketa Germany
Dale Muzzey United States
Brian E. Hall United States
Léon Espinosa France
Srinivas Ramachandran United States
Christopher T. Eggers United States
Gianluca Pegoraro
Citations per year, relative to Gianluca Pegoraro Gianluca Pegoraro (= 1×) peers Christopher T. Eggers

Countries citing papers authored by Gianluca Pegoraro

Since Specialization
Citations

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

Fields of papers citing papers by Gianluca Pegoraro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gianluca Pegoraro

This figure shows the co-authorship network connecting the top 25 collaborators of Gianluca Pegoraro. A scholar is included among the top collaborators of Gianluca Pegoraro 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 Gianluca Pegoraro. Gianluca Pegoraro 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.
Keikhosravi, Adib, et al.. (2025). Orderly mitosis shapes interphase genome architecture. eLife.
3.
Keikhosravi, Adib, et al.. (2025). Simulation and Quantitative Analysis of Spatial Centromere Distribution Patterns. Cells. 14(7). 491–491. 1 indexed citations
4.
Keikhosravi, Adib, Christopher H. Bohrer, Nadezda A. Fursova, et al.. (2024). High-throughput image processing software for the study of nuclear architecture and gene expression. Scientific Reports. 14(1). 18426–18426. 4 indexed citations
5.
Shilo, Asaf, Gianluca Pegoraro, & Tom Misteli. (2024). High-Throughput RNA-HCR-FISH Detection of Endogenous Pre-mRNA Splice Variants. Methods in molecular biology. 2784. 133–146.
6.
Gadkari, Manasi, et al.. (2024). hcHCR: High-Throughput Single-Cell Imaging of RNA in Human Primary Immune Cells. Methods in molecular biology. 2784. 113–132. 1 indexed citations
7.
Shrestha, Roshan L., Laurent Ozbun, Raj Chari, et al.. (2023). The histone H3/H4 chaperone CHAF1B prevents the mislocalization of CENP-A for chromosomal stability. Journal of Cell Science. 136(10). 8 indexed citations
8.
Shilo, Asaf, Gianluca Pegoraro, & Tom Misteli. (2022). HiFENS: high-throughput FISH detection of endogenous pre-mRNA splicing isoforms. Nucleic Acids Research. 50(22). e130–e130. 3 indexed citations
9.
Rosin, Leah F., et al.. (2022). NURF301 contributes to gypsy chromatin insulator-mediated nuclear organization. Nucleic Acids Research. 50(14). 7906–7924. 5 indexed citations
10.
Rinaldi, Lorenzo, Grégory Fettweis, Sohyoung Kim, et al.. (2022). The glucocorticoid receptor associates with the cohesin loader NIPBL to promote long-range gene regulation. Science Advances. 8(13). eabj8360–eabj8360. 30 indexed citations
11.
Stavreva, Diana A., David A. Garcia, Grégory Fettweis, et al.. (2019). Transcriptional Bursting and Co-bursting Regulation by Steroid Hormone Release Pattern and Transcription Factor Mobility. Molecular Cell. 75(6). 1161–1177.e11. 89 indexed citations
12.
Pegoraro, Gianluca, et al.. (2017). HiHiMap: single-cell quantitation of histones and histone posttranslational modifications across the cell cycle by high-throughput imaging. Molecular Biology of the Cell. 28(17). 2290–2302. 13 indexed citations
13.
Gudla, Prabhakar R., Koh Nakayama, Gianluca Pegoraro, & Tom Misteli. (2017). SpotLearn: Convolutional Neural Network for Detection of Fluorescence In Situ Hybridization (FISH) Signals in High-Throughput Imaging Approaches. Cold Spring Harbor Symposia on Quantitative Biology. 82. 57–70. 34 indexed citations
14.
Radoshitzky, Sheli R., Gianluca Pegoraro, Xiǎolì Chī, et al.. (2016). siRNA Screen Identifies Trafficking Host Factors that Modulate Alphavirus Infection. PLoS Pathogens. 12(3). e1005466–e1005466. 31 indexed citations
15.
Zong, Dali, et al.. (2015). Ectopic expression of RNF168 and 53BP1 increases mutagenic but not physiological non-homologous end joining. Nucleic Acids Research. 43(10). 4950–4961. 22 indexed citations
16.
Shachar, Sigal, Gianluca Pegoraro, & Tom Misteli. (2015). HIPMap: A High-Throughput Imaging Method for Mapping Spatial Gene Positions. Cold Spring Harbor Symposia on Quantitative Biology. 80. 73–81. 24 indexed citations
17.
Burman, Bharat, et al.. (2015). Histone modifications predispose genome regions to breakage and translocation. Genes & Development. 29(13). 1393–1402. 41 indexed citations
18.
Garrison, Aura R., Sheli R. Radoshitzky, Krishna P. Kota, et al.. (2013). Crimean–Congo hemorrhagic fever virus utilizes a clathrin- and early endosome-dependent entry pathway. Virology. 444(1-2). 45–54. 57 indexed citations
19.
Pegoraro, Gianluca, et al.. (2012). Identification of Mammalian Protein Quality Control Factors by High-Throughput Cellular Imaging. PLoS ONE. 7(2). e31684–e31684. 17 indexed citations
20.
Pegoraro, Gianluca, et al.. (2009). Ageing-related chromatin defects through loss of the NURD complex. Nature Cell Biology. 11(10). 1261–1267. 216 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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