Katherine M. Aird

4.8k total citations · 2 hit papers
58 papers, 3.0k citations indexed

About

Katherine M. Aird is a scholar working on Molecular Biology, Cancer Research and Physiology. According to data from OpenAlex, Katherine M. Aird has authored 58 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Molecular Biology, 16 papers in Cancer Research and 15 papers in Physiology. Recurrent topics in Katherine M. Aird's work include Telomeres, Telomerase, and Senescence (15 papers), Cancer, Hypoxia, and Metabolism (12 papers) and DNA Repair Mechanisms (10 papers). Katherine M. Aird is often cited by papers focused on Telomeres, Telomerase, and Senescence (15 papers), Cancer, Hypoxia, and Metabolism (12 papers) and DNA Repair Mechanisms (10 papers). Katherine M. Aird collaborates with scholars based in United States, Russia and China. Katherine M. Aird's co-authors include Rugang Zhang, Benjamin G. Bitler, Andrew V. Kossenkov, David W. Speicher, Raquel Buj, Qin Liu, Azat Garipov, D. Schultz, Gayathri R. Devi and José R. Conejo-García and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Medicine and Nature Communications.

In The Last Decade

Katherine M. Aird

58 papers receiving 3.0k citations

Hit Papers

Synthetic lethality by targeting EZH2 methyltransferase a... 2015 2026 2018 2022 2015 2019 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
Katherine M. Aird United States 29 2.1k 659 658 554 406 58 3.0k
Stéphanie Gaillard United States 28 1.8k 0.8× 1.2k 1.8× 370 0.6× 199 0.4× 420 1.0× 103 3.2k
Dimcho Bachvarov Canada 34 1.9k 0.9× 582 0.9× 439 0.7× 223 0.4× 777 1.9× 91 3.9k
Jianbiao Zhou Singapore 34 2.2k 1.1× 694 1.1× 705 1.1× 322 0.6× 547 1.3× 81 3.5k
Markus Christmann Germany 37 3.4k 1.6× 1.2k 1.7× 1.2k 1.8× 238 0.4× 323 0.8× 84 4.5k
Dimitris Athineos United Kingdom 26 2.6k 1.2× 1.2k 1.9× 996 1.5× 192 0.3× 445 1.1× 36 3.7k
José Palacios Spain 26 1.5k 0.7× 870 1.3× 441 0.7× 226 0.4× 142 0.3× 58 2.9k
Ker Yu United States 36 3.3k 1.6× 631 1.0× 570 0.9× 310 0.6× 477 1.2× 84 4.5k
Ryan J.O. Dowling Canada 19 3.9k 1.9× 1.6k 2.5× 1.1k 1.6× 302 0.5× 362 0.9× 29 4.8k
Phillip Buckhaults United States 27 2.6k 1.2× 1.1k 1.6× 592 0.9× 196 0.4× 634 1.6× 50 3.6k
Alessandro Cama Italy 33 1.9k 0.9× 748 1.1× 529 0.8× 261 0.5× 102 0.3× 147 3.8k

Countries citing papers authored by Katherine M. Aird

Since Specialization
Citations

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

Fields of papers citing papers by Katherine M. Aird

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Katherine M. Aird. 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 Katherine M. Aird. The network helps show where Katherine M. Aird may publish in the future.

Co-authorship network of co-authors of Katherine M. Aird

This figure shows the co-authorship network connecting the top 25 collaborators of Katherine M. Aird. A scholar is included among the top collaborators of Katherine M. Aird 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 Katherine M. Aird. Katherine M. Aird 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.
Sharrow, Allison C., Emily Megill, Nadine Hempel, et al.. (2024). Acetate drives ovarian cancer quiescence via ACSS2-mediated acetyl-CoA production. Molecular Metabolism. 89. 102031–102031. 1 indexed citations
2.
Aird, Katherine M., et al.. (2024). Interplay between altered metabolism and DNA damage and repair in ovarian cancer. BioEssays. 46(8). e2300166–e2300166. 4 indexed citations
3.
Buj, Raquel, Jiefei Wang, Aidan R. Cole, et al.. (2024). De Novo Purine Metabolism is a Metabolic Vulnerability of Cancers with Low p16 Expression. Cancer Research Communications. 4(5). 1174–1188. 4 indexed citations
4.
Oesterreich, Steffi & Katherine M. Aird. (2023). Senescence and Immunotherapy: Redundant Immunomodulatory Pathways Promote Resistance. Cancer Immunology Research. 11(4). 401–404. 6 indexed citations
5.
Airik, Merlin, Chi‐Wei Chen, Katherine M. Aird, et al.. (2023). Mitochondrial ROS Triggers KIN Pathogenesis in FAN1-Deficient Kidneys. Antioxidants. 12(4). 900–900. 5 indexed citations
6.
Huang, Zhentai, Chi‐Wei Chen, Raquel Buj, et al.. (2022). ATM inhibition drives metabolic adaptation via induction of macropinocytosis. The Journal of Cell Biology. 222(1). 10 indexed citations
7.
Leon, Kelly E., et al.. (2021). Loss of p16: A Bouncer of the Immunological Surveillance?. Life. 11(4). 309–309. 13 indexed citations
8.
Buj, Raquel, et al.. (2021). Suppression of p16 alleviates the senescence-associated secretory phenotype. Aging. 13(3). 3290–3312. 47 indexed citations
9.
Leon, Kelly E., Raquel Buj, Chi‐Wei Chen, et al.. (2021). DOT1L modulates the senescence-associated secretory phenotype through epigenetic regulation of IL1A. The Journal of Cell Biology. 220(8). 41 indexed citations
10.
Cole, Alexander J., M. R. S. Iyengar, Patrick O’Hayer, et al.. (2020). NFATC4 promotes quiescence and chemotherapy resistance in ovarian cancer. JCI Insight. 5(7). 32 indexed citations
11.
Chen, Chi‐Wei, et al.. (2020). ATM inhibition synergizes with fenofibrate in high grade serous ovarian cancer cells. Heliyon. 6(9). e05097–e05097. 9 indexed citations
12.
Zhao, Bo, Pingyu Liu, Takeshi Fukumoto, et al.. (2020). Topoisomerase 1 cleavage complex enables pattern recognition and inflammation during senescence. Nature Communications. 11(1). 908–908. 51 indexed citations
13.
Nacarelli, Timothy, Lena Lau, Takeshi Fukumoto, et al.. (2019). NAD+ metabolism governs the proinflammatory senescence-associated secretome. Nature Cell Biology. 21(3). 397–407. 282 indexed citations breakdown →
14.
Leon, Kelly E. & Katherine M. Aird. (2019). Jumonji C Demethylases in Cellular Senescence. Genes. 10(1). 33–33. 14 indexed citations
15.
Harper, Sandra L., Aaron R. Goldman, Benjamin G. Bitler, et al.. (2018). CLIC1 and CLIC4 complement CA125 as a diagnostic biomarker panel for all subtypes of epithelial ovarian cancer. Scientific Reports. 8(1). 14725–14725. 33 indexed citations
16.
Fatkhutdinov, Nail, Katrin Sproesser, Clemens Krepler, et al.. (2016). Targeting RRM2 and Mutant BRAF Is a Novel Combinatorial Strategy for Melanoma. Molecular Cancer Research. 14(9). 767–775. 23 indexed citations
17.
Aird, Katherine M., Osamu Iwasaki, Andrew V. Kossenkov, et al.. (2016). HMGB2 orchestrates the chromatin landscape of senescence-associated secretory phenotype gene loci. The Journal of Cell Biology. 215(3). 325–334. 129 indexed citations
18.
Zhang, Jing, Chengyang Wang, Xi Chen, et al.. (2015). EglN2 associates with the NRF 1‐ PGC 1α complex and controls mitochondrial function in breast cancer. The EMBO Journal. 34(23). 2953–2970. 59 indexed citations
19.
Aird, Katherine M., et al.. (2010). X-Linked Inhibitor of Apoptosis Protein Inhibits Apoptosis in Inflammatory Breast Cancer Cells with Acquired Resistance to an ErbB1/2 Tyrosine Kinase Inhibitor. Molecular Cancer Therapeutics. 9(5). 1432–1442. 63 indexed citations
20.
Aird, Katherine M., Aris Baras, Jun-Ping Wei, et al.. (2008). Trastuzumab signaling in ErbB2-overexpressing inflammatory breast cancer correlates with X-linked inhibitor of apoptosis protein expression. Molecular Cancer Therapeutics. 7(1). 38–47. 54 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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