Nicolas L. Young

5.0k total citations · 1 hit paper
59 papers, 2.9k citations indexed

About

Nicolas L. Young is a scholar working on Molecular Biology, Spectroscopy and Oncology. According to data from OpenAlex, Nicolas L. Young has authored 59 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Molecular Biology, 17 papers in Spectroscopy and 3 papers in Oncology. Recurrent topics in Nicolas L. Young's work include Genomics and Chromatin Dynamics (25 papers), Epigenetics and DNA Methylation (16 papers) and Advanced Proteomics Techniques and Applications (15 papers). Nicolas L. Young is often cited by papers focused on Genomics and Chromatin Dynamics (25 papers), Epigenetics and DNA Methylation (16 papers) and Advanced Proteomics Techniques and Applications (15 papers). Nicolas L. Young collaborates with scholars based in United States, Germany and Japan. Nicolas L. Young's co-authors include Benjamin A. García, Mariana D. Plazas-Mayorca, Peter A. DiMaggio, Gary LeRoy, Barry M. Zee, Christodoulos A. Floudas, Richard C. Baliban, Michael A. Freitas, Matthew V. Holt and Sean W. Harshman and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Nicolas L. Young

58 papers receiving 2.9k citations

Hit Papers

SIRT7 links H3K18 deacetylation to maintenance of oncogen... 2012 2026 2016 2021 2012 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
Nicolas L. Young United States 28 2.2k 490 339 287 240 59 2.9k
Michael Rehman Italy 14 3.4k 1.5× 243 0.5× 471 1.4× 380 1.3× 886 3.7× 16 4.1k
Dorte B. Bekker‐Jensen Denmark 20 2.3k 1.0× 1.2k 2.4× 110 0.3× 149 0.5× 360 1.5× 24 3.0k
Yoonjung Kho United States 11 1.4k 0.6× 219 0.4× 418 1.2× 252 0.9× 373 1.6× 16 1.9k
Kristie L. Rose United States 21 867 0.4× 298 0.6× 101 0.3× 297 1.0× 86 0.4× 46 1.5k
Fulai Jin United States 20 3.3k 1.5× 112 0.2× 135 0.4× 152 0.5× 254 1.1× 30 3.8k
Damian Fermin United States 13 889 0.4× 153 0.3× 125 0.4× 114 0.4× 142 0.6× 28 1.3k
Tzuling Cheng United States 10 3.1k 1.4× 137 0.3× 437 1.3× 526 1.8× 603 2.5× 15 4.3k
Heiko Horn Denmark 14 1.2k 0.5× 147 0.3× 63 0.2× 94 0.3× 226 0.9× 20 1.5k
Taras Stasyk Austria 25 1.5k 0.7× 520 1.1× 20 0.1× 300 1.0× 226 0.9× 44 2.3k
Laura Pontano Vaites United States 14 1.4k 0.6× 204 0.4× 23 0.1× 357 1.2× 222 0.9× 17 2.2k

Countries citing papers authored by Nicolas L. Young

Since Specialization
Citations

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

Fields of papers citing papers by Nicolas L. Young

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nicolas L. Young. 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 Nicolas L. Young. The network helps show where Nicolas L. Young may publish in the future.

Co-authorship network of co-authors of Nicolas L. Young

This figure shows the co-authorship network connecting the top 25 collaborators of Nicolas L. Young. A scholar is included among the top collaborators of Nicolas L. Young 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 Nicolas L. Young. Nicolas L. Young 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.
Phillips, Margaret, Brian Boyle, Cameron Montgomery, et al.. (2024). Impact of Combinatorial Histone Modifications on Acetyllysine Recognition by the ATAD2 and ATAD2B Bromodomains. Journal of Medicinal Chemistry. 67(10). 8186–8200. 3 indexed citations
3.
Young, Nicolas L., et al.. (2024). Histone H3K18 & H3K23 acetylation directs establishment of MLL-mediated H3K4 methylation. UNC Libraries. 1 indexed citations
4.
Young, Nicolas L. & Ruhee Dere. (2021). Mechanistic insights into KDM4A driven genomic instability. Biochemical Society Transactions. 49(1). 93–105. 18 indexed citations
5.
Park, Kyung‐Won, et al.. (2021). Gene therapy using Aβ variants for amyloid reduction. Molecular Therapy. 29(7). 2294–2307. 5 indexed citations
6.
Hu, Tianyuan, Xiangguo Shi, Ayumi Kitano, et al.. (2019). AMP-activated protein kinase links acetyl-CoA homeostasis to BRD4 recruitment in acute myeloid leukemia. Blood. 134(24). 2183–2194. 34 indexed citations
7.
Holt, Matthew V., et al.. (2018). The histone H4 proteoform dynamics in response to SUV4-20 inhibition reveals single molecule mechanisms of inhibitor resistance. Epigenetics & Chromatin. 11(1). 29–29. 28 indexed citations
8.
Fang, Pengfei, et al.. (2017). Mapping the contact surfaces in the Lamin A:AIMP3 complex by hydrogen/deuterium exchange FT-ICR mass spectrometry. PLoS ONE. 12(8). e0181869–e0181869. 4 indexed citations
9.
Guo, Yusong R., Yuan Wang, Ying Zhou, et al.. (2017). Structure of a pentameric virion-associated fiber with a potential role in Orsay virus entry to host cells. PLoS Pathogens. 13(2). e1006231–e1006231. 13 indexed citations
10.
12.
Guan, Xiaoyan, et al.. (2015). Quantitative Mass Spectrometry Reveals that Intact Histone H1 Phosphorylations are Variant Specific and Exhibit Single Molecule Hierarchical Dependence. Molecular & Cellular Proteomics. 15(3). 818–833. 27 indexed citations
13.
Voigt, Philipp, Gary LeRoy, William J. Drury, et al.. (2012). Asymmetrically Modified Nucleosomes. Cell. 151(1). 181–193. 317 indexed citations
14.
Zee, Barry M., Nicolas L. Young, & Benjamin A. García. (2011). Quantitative Proteomic Approaches to Studying Histone Modifications. PubMed. 5(Suppl 1). 106–114. 12 indexed citations
15.
Yan, Kai‐Lin, Qiang Cao, Christopher M. Reilly, et al.. (2011). Histone Deacetylase 9 Deficiency Protects against Effector T Cell-mediated Systemic Autoimmunity. Journal of Biological Chemistry. 286(33). 28833–28843. 81 indexed citations
16.
Plazas-Mayorca, Mariana D., Joshua S. Bloom, Ulrike Zeißler, et al.. (2010). Quantitative proteomics reveals direct and indirect alterations in the histone code following methyltransferase knockdown. Molecular BioSystems. 6(9). 1719–1729. 29 indexed citations
17.
Baliban, Richard C., Peter A. DiMaggio, Mariana D. Plazas-Mayorca, et al.. (2010). A Novel Approach for Untargeted Post-translational Modification Identification Using Integer Linear Optimization and Tandem Mass Spectrometry. Molecular & Cellular Proteomics. 9(5). 764–779. 39 indexed citations
18.
Young, Nicolas L., Peter A. DiMaggio, & Benjamin A. García. (2010). The significance, development and progress of high-throughput combinatorial histone code analysis. Cellular and Molecular Life Sciences. 67(23). 3983–4000. 83 indexed citations
19.
Xie, Wei, Chunying Song, Nicolas L. Young, et al.. (2009). Histone H3 Lysine 56 Acetylation Is Linked to the Core Transcriptional Network in Human Embryonic Stem Cells. Molecular Cell. 33(4). 417–427. 160 indexed citations
20.
Young, Nicolas L., Peter A. DiMaggio, Mariana D. Plazas-Mayorca, et al.. (2009). High Throughput Characterization of Combinatorial Histone Codes. Molecular & Cellular Proteomics. 8(10). 2266–2284. 248 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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