Andrew J. Andrews

4.2k total citations · 1 hit paper
48 papers, 3.1k citations indexed

About

Andrew J. Andrews is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Andrew J. Andrews has authored 48 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Molecular Biology, 9 papers in Oncology and 5 papers in Cancer Research. Recurrent topics in Andrew J. Andrews's work include Genomics and Chromatin Dynamics (17 papers), Epigenetics and DNA Methylation (13 papers) and Histone Deacetylase Inhibitors Research (9 papers). Andrew J. Andrews is often cited by papers focused on Genomics and Chromatin Dynamics (17 papers), Epigenetics and DNA Methylation (13 papers) and Histone Deacetylase Inhibitors Research (9 papers). Andrew J. Andrews collaborates with scholars based in United States, United Kingdom and Russia. Andrew J. Andrews's co-authors include Karolin Luger, Yin‐Ming Kuo, Ryan A. Henry, Ian Rosewell, Gordon Stamp, Clive Dickson, Vera Fantl, Laurie A. Stargell, Alexander S. Zevin and Xu Chen and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Nucleic Acids Research.

In The Last Decade

Andrew J. Andrews

48 papers receiving 3.0k citations

Hit Papers

Mice lacking cyclin D1 are small and show defects in eye ... 1995 2026 2005 2015 1995 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andrew J. Andrews United States 26 2.4k 566 354 224 216 48 3.1k
Katherine M. Hannan Australia 30 2.9k 1.2× 668 1.2× 348 1.0× 160 0.7× 152 0.7× 64 3.6k
Venkatesha Basrur United States 30 2.5k 1.0× 471 0.8× 331 0.9× 179 0.8× 366 1.7× 86 3.2k
Takeo Narita Japan 21 2.3k 1.0× 700 1.2× 285 0.8× 237 1.1× 200 0.9× 48 2.9k
Mikhail A. Nikiforov United States 30 2.1k 0.9× 580 1.0× 486 1.4× 269 1.2× 144 0.7× 69 2.8k
Samuel G. Mackintosh United States 30 2.2k 0.9× 290 0.5× 210 0.6× 230 1.0× 203 0.9× 79 2.9k
Tsuyoshi Ikura Japan 31 3.4k 1.4× 705 1.2× 420 1.2× 156 0.7× 324 1.5× 61 3.9k
Rieko Ohki Japan 21 2.3k 1.0× 1.2k 2.2× 445 1.3× 266 1.2× 194 0.9× 50 3.0k
Kam C. Yeung United States 31 3.0k 1.3× 644 1.1× 453 1.3× 143 0.6× 193 0.9× 52 3.8k
Françesc Canals Spain 28 1.5k 0.6× 420 0.7× 278 0.8× 135 0.6× 147 0.7× 97 2.5k

Countries citing papers authored by Andrew J. Andrews

Since Specialization
Citations

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

Fields of papers citing papers by Andrew J. Andrews

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew J. Andrews. 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 Andrew J. Andrews. The network helps show where Andrew J. Andrews may publish in the future.

Co-authorship network of co-authors of Andrew J. Andrews

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew J. Andrews. A scholar is included among the top collaborators of Andrew J. Andrews 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 Andrew J. Andrews. Andrew J. Andrews 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.
Plumley, John B., Arnold L. Rheingold, Peter I. Djurovich, et al.. (2022). Benchmarking the dynamic luminescence properties and UV stability of B 18 H 22 -based materials. Dalton Transactions. 51(24). 9223–9228. 5 indexed citations
2.
Lowe, Brandon R., Rajesh Kumar Yadav, Ryan A. Henry, et al.. (2021). Surprising phenotypic diversity of cancer-associated mutations of Gly 34 in the histone H3 tail. eLife. 10. 28 indexed citations
3.
Henry, Ryan A., Yin‐Ming Kuo, Tim J. Yen, et al.. (2019). Discordant Effects of Putative Lysine Acetyltransferase Inhibitors in Biochemical and Living Systems. Cells. 8(9). 1022–1022. 3 indexed citations
4.
Kuo, Yin‐Ming, et al.. (2019). Two factor authentication: Asf1 mediates crosstalk between H3 K14 and K56 acetylation. Nucleic Acids Research. 47(14). 7380–7391. 19 indexed citations
5.
Sidoli, Simone, Mariana Lopes, Zuo‐Fei Yuan, et al.. (2019). One minute analysis of 200 histone posttranslational modifications by direct injection mass spectrometry. Genome Research. 29(6). 978–987. 42 indexed citations
6.
Gordon, Renata E., Li Zhang, Suraj Peri, et al.. (2018). Statins Synergize with Hedgehog Pathway Inhibitors for Treatment of Medulloblastoma. Clinical Cancer Research. 24(6). 1375–1388. 53 indexed citations
7.
Duong‐Ly, Krisna C., Yin‐Ming Kuo, Matthew C. Johnson, et al.. (2018). T cell activation triggers reversible inosine-5′-monophosphate dehydrogenase assembly. Journal of Cell Science. 131(17). 38 indexed citations
8.
Li, Xinyuan, Ying Shao, Xiaojin Sha, et al.. (2018). IL-35 (Interleukin-35) Suppresses Endothelial Cell Activation by Inhibiting Mitochondrial Reactive Oxygen Species-Mediated Site-Specific Acetylation of H3K14 (Histone 3 Lysine 14). Arteriosclerosis Thrombosis and Vascular Biology. 38(3). 599–609. 79 indexed citations
9.
10.
Semenova, Galina, Yin‐Ming Kuo, Andrew J. Andrews, et al.. (2017). An Essential Role for the Tumor-Suppressor Merlin in Regulating Fatty Acid Synthesis. Cancer Research. 77(18). 5026–5038. 20 indexed citations
11.
Kuo, Yin‐Ming, et al.. (2017). HDAC8 substrate selectivity is determined by long- and short-range interactions leading to enhanced reactivity for full-length histone substrates compared with peptides. Journal of Biological Chemistry. 292(52). 21568–21577. 32 indexed citations
12.
Carrer, Alessandro, Joshua L.D. Parris, Sophie Trefely, et al.. (2017). Impact of a High-fat Diet on Tissue Acyl-CoA and Histone Acetylation Levels. Journal of Biological Chemistry. 292(8). 3312–3322. 124 indexed citations
13.
Kuo, Yin‐Ming, Ryan A. Henry, Song Tan, Jacques Côté, & Andrew J. Andrews. (2015). Site specificity analysis of Piccolo NuA4-mediated acetylation for different histone complexes. Biochemical Journal. 472(2). 239–248. 7 indexed citations
15.
Kuo, Yin‐Ming & Andrew J. Andrews. (2013). Quantitating the Specificity and Selectivity of Gcn5-Mediated Acetylation of Histone H3. PLoS ONE. 8(2). e54896–e54896. 85 indexed citations
16.
Henry, Ryan A., Yin‐Ming Kuo, & Andrew J. Andrews. (2013). Differences in Specificity and Selectivity Between CBP and p300 Acetylation of Histone H3 and H3/H4. Biochemistry. 52(34). 5746–5759. 128 indexed citations
17.
Andrews, Andrew J. & Karolin Luger. (2010). A Coupled Equilibrium Approach to Study Nucleosome Thermodynamics. Methods in enzymology on CD-ROM/Methods in enzymology. 488. 265–285. 16 indexed citations
18.
Koutmou, Kristin S., Anette Casiano‐Negroni, Samuel Pazicni, et al.. (2010). NMR and XAS reveal an inner-sphere metal binding site in the P4 helix of the metallo-ribozyme ribonuclease P. Proceedings of the National Academy of Sciences. 107(6). 2479–2484. 18 indexed citations
19.
Andrews, Andrew J., et al.. (2008). A Thermodynamic Model for Nap1-Histone Interactions. Journal of Biological Chemistry. 283(47). 32412–32418. 75 indexed citations
20.
Park, Young‐Jun, et al.. (2008). Histone chaperone specificity in Rtt109 activation. Nature Structural & Molecular Biology. 15(9). 957–964. 58 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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