Rosemary Yu

1.7k total citations · 1 hit paper
19 papers, 1.2k citations indexed

About

Rosemary Yu is a scholar working on Molecular Biology, Cancer Research and Surgery. According to data from OpenAlex, Rosemary Yu has authored 19 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 6 papers in Cancer Research and 4 papers in Surgery. Recurrent topics in Rosemary Yu's work include Microbial Metabolic Engineering and Bioproduction (9 papers), Fungal and yeast genetics research (7 papers) and Cancer, Lipids, and Metabolism (6 papers). Rosemary Yu is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (9 papers), Fungal and yeast genetics research (7 papers) and Cancer, Lipids, and Metabolism (6 papers). Rosemary Yu collaborates with scholars based in Sweden, Denmark and Canada. Rosemary Yu's co-authors include Linda Z. Penn, Peter Mullen, Joseph Longo, Michael C. Archer, Herb E. Schellhorn, Jens Nielsen, Tao Dong, Carl Malina, Jenna E. van Leeuwen and Kate Campbell and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Nature reviews. Cancer.

In The Last Decade

Rosemary Yu

19 papers receiving 1.1k citations

Hit Papers

The interplay between cell signalling and the mevalonate ... 2016 2026 2019 2022 2016 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
Rosemary Yu Sweden 15 687 523 248 152 129 19 1.2k
Weidan Ji China 19 945 1.4× 519 1.0× 74 0.3× 87 0.6× 252 2.0× 32 1.3k
Biagio Pucci Italy 19 614 0.9× 189 0.4× 78 0.3× 127 0.8× 141 1.1× 33 918
Fabao Liu China 19 1.0k 1.5× 575 1.1× 82 0.3× 66 0.4× 141 1.1× 27 1.4k
Eiji Furuta United States 15 1.1k 1.5× 624 1.2× 100 0.4× 113 0.7× 294 2.3× 19 1.5k
Zizheng Dong United States 25 1.2k 1.8× 348 0.7× 81 0.3× 101 0.7× 488 3.8× 49 1.6k
Kin Chan Hong Kong 19 1.1k 1.6× 551 1.1× 112 0.5× 119 0.8× 277 2.1× 38 1.6k
Xinying Wang China 24 807 1.2× 421 0.8× 138 0.6× 162 1.1× 483 3.7× 68 1.5k
Minghui He China 15 862 1.3× 254 0.5× 49 0.2× 104 0.7× 113 0.9× 35 1.3k
Bingtao Hao China 23 1.4k 2.0× 316 0.6× 87 0.4× 77 0.5× 383 3.0× 76 1.9k

Countries citing papers authored by Rosemary Yu

Since Specialization
Citations

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

Fields of papers citing papers by Rosemary Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rosemary Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Rosemary Yu. A scholar is included among the top collaborators of Rosemary Yu 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 Rosemary Yu. Rosemary Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
1.
Sánchez, Benjamín J., Petri‐Jaan Lahtvee, Kate Campbell, et al.. (2021). Benchmarking accuracy and precision of intensity‐based absolute quantification of protein abundances in Saccharomyces cerevisiae. PROTEOMICS. 21(6). e2000093–e2000093. 12 indexed citations
2.
Yu, Rosemary, Egor Vorontsov, Carina Sihlbom, & Jens Nielsen. (2021). Quantifying absolute gene expression profiles reveals distinct regulation of central carbon metabolism genes in yeast. eLife. 10. 20 indexed citations
3.
Yu, Rosemary, et al.. (2021). A single chromosome strain of S. cerevisiae exhibits diminished ethanol metabolism and tolerance. BMC Genomics. 22(1). 688–688. 3 indexed citations
4.
Yu, Rosemary, Joseph Longo, Jenna E. van Leeuwen, et al.. (2021). Mevalonate Pathway Inhibition Slows Breast Cancer Metastasis via Reduced N-glycosylation Abundance and Branching. Cancer Research. 81(10). 2625–2635. 29 indexed citations
5.
Lu, Hongzhong, Feiran Li, Le Yuan, et al.. (2021). Yeast metabolic innovations emerged via expanded metabolic network and gene positive selection. Molecular Systems Biology. 17(10). e10427–e10427. 28 indexed citations
6.
Malina, Carl, et al.. (2021). Adaptations in metabolism and protein translation give rise to the Crabtree effect in yeast. Proceedings of the National Academy of Sciences. 118(51). 56 indexed citations
7.
Yu, Rosemary, Kate Campbell, Rui Pereira, et al.. (2020). Nitrogen limitation reveals large reserves in metabolic and translational capacities of yeast. Nature Communications. 11(1). 1881–1881. 53 indexed citations
8.
Campbell, Kate, et al.. (2020). Proteome reallocation from amino acid biosynthesis to ribosomes enables yeast to grow faster in rich media. Proceedings of the National Academy of Sciences. 117(35). 21804–21812. 42 indexed citations
9.
Li, Feiran, Rosemary Yu, Martin K. M. Engqvist, et al.. (2020). Different Routes of Protein Folding Contribute to Improved Protein Production in Saccharomyces cerevisiae. mBio. 11(6). 19 indexed citations
10.
Yu, Rosemary & Jens Nielsen. (2019). Yeast systems biology in understanding principles of physiology underlying complex human diseases. Current Opinion in Biotechnology. 63. 63–69. 8 indexed citations
11.
Yu, Rosemary & Jens Nielsen. (2019). Big data in yeast systems biology. FEMS Yeast Research. 19(7). 12 indexed citations
12.
Longo, Joseph, Peter Mullen, Rosemary Yu, et al.. (2019). An actionable sterol-regulated feedback loop modulates statin sensitivity in prostate cancer. Molecular Metabolism. 25. 119–130. 63 indexed citations
13.
Yu, Rosemary, Joseph Longo, Jenna E. van Leeuwen, et al.. (2017). Statin-Induced Cancer Cell Death Can Be Mechanistically Uncoupled from Prenylation of RAS Family Proteins. Cancer Research. 78(5). 1347–1357. 53 indexed citations
14.
Mullen, Peter, Rosemary Yu, Joseph Longo, Michael C. Archer, & Linda Z. Penn. (2016). The interplay between cell signalling and the mevalonate pathway in cancer. Nature reviews. Cancer. 16(11). 718–731. 489 indexed citations breakdown →
15.
Pandyra, Aleksandra A., Peter Mullen, Carolyn A. Goard, et al.. (2015). Genome-wide RNAi analysis reveals that simultaneous inhibition of specific mevalonate pathway genes potentiates tumor cell death. Oncotarget. 6(29). 26909–26921. 51 indexed citations
16.
Pandyra, Aleksandra A., Peter Mullen, Manpreet Kalkat, et al.. (2014). Immediate Utility of Two Approved Agents to Target Both the Metabolic Mevalonate Pathway and Its Restorative Feedback Loop. Cancer Research. 74(17). 4772–4782. 64 indexed citations
17.
Yu, Rosemary & Herb E. Schellhorn. (2012). Recent Applications of Engineered Animal Antioxidant Deficiency Models in Human Nutrition and Chronic Disease. Journal of Nutrition. 143(1). 1–11. 31 indexed citations
18.
Dong, Tao, Rosemary Yu, & Herb E. Schellhorn. (2010). Antagonistic regulation of motility and transcriptome expression by RpoN and RpoS in Escherichia coli. Molecular Microbiology. 79(2). 375–386. 83 indexed citations
19.
Dong, Tao, et al.. (2009). Polymorphism and selection of rpoS in pathogenic Escherichia coli. BMC Microbiology. 9(1). 118–118. 39 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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