Allison C. Sharrow

1.4k total citations · 1 hit paper
16 papers, 1.0k citations indexed

About

Allison C. Sharrow is a scholar working on Molecular Biology, Immunology and Cancer Research. According to data from OpenAlex, Allison C. Sharrow has authored 16 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 5 papers in Immunology and 5 papers in Cancer Research. Recurrent topics in Allison C. Sharrow's work include Bone Metabolism and Diseases (5 papers), Cancer, Hypoxia, and Metabolism (2 papers) and Cancer Cells and Metastasis (2 papers). Allison C. Sharrow is often cited by papers focused on Bone Metabolism and Diseases (5 papers), Cancer, Hypoxia, and Metabolism (2 papers) and Cancer Cells and Metastasis (2 papers). Allison C. Sharrow collaborates with scholars based in United States, Italy and China. Allison C. Sharrow's co-authors include Harry C. Blair, Beatrice B. Yaroslavskiy, Mone Zaidi, Li Sun, Zhiyuan Zhang, Yuanzhen Peng, Lingling Zhu, Bo Wei, Dionysios J. Papachristou and T. Rajendra Kumar and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and ACS Nano.

In The Last Decade

Allison C. Sharrow

16 papers receiving 1.0k citations

Hit Papers

FSH Directly Regulates Bone Mass 2006 2026 2012 2019 2006 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
Allison C. Sharrow United States 12 559 238 208 200 187 16 1.0k
Beatrice B. Yaroslavskiy United States 15 681 1.2× 365 1.5× 234 1.1× 232 1.2× 253 1.4× 21 1.3k
Tamás Czömpöly Hungary 18 266 0.5× 186 0.8× 127 0.6× 360 1.8× 33 0.2× 41 973
Din‐Lii Lin United States 9 381 0.7× 212 0.9× 183 0.9× 158 0.8× 61 0.3× 13 730
D. W. Burton United States 23 599 1.1× 447 1.9× 103 0.5× 199 1.0× 90 0.5× 38 1.2k
Juan A. Ardura Spain 19 687 1.2× 287 1.2× 82 0.4× 52 0.3× 91 0.5× 35 1.1k
Weston P. Miller United States 25 814 1.5× 199 0.8× 211 1.0× 53 0.3× 24 0.1× 72 1.7k
Haig Aghajanian United States 20 983 1.8× 180 0.8× 144 0.7× 38 0.2× 6 0.0× 27 1.6k
Elisheva Smith United States 13 900 1.6× 262 1.1× 248 1.2× 107 0.5× 107 0.6× 14 1.2k
Xiao Hui Liao United States 10 574 1.0× 82 0.3× 150 0.7× 278 1.4× 9 0.0× 15 1.0k
Sung Yoon Cho South Korea 19 260 0.5× 45 0.2× 322 1.5× 133 0.7× 14 0.1× 105 939

Countries citing papers authored by Allison C. Sharrow

Since Specialization
Citations

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

Fields of papers citing papers by Allison C. Sharrow

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Allison C. Sharrow. 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 Allison C. Sharrow. The network helps show where Allison C. Sharrow may publish in the future.

Co-authorship network of co-authors of Allison C. Sharrow

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

All Works

16 of 16 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.
Rutte, Joseph de, Robert Dimatteo, Maani M. Archang, et al.. (2022). Suspendable Hydrogel Nanovials for Massively Parallel Single-Cell Functional Analysis and Sorting. ACS Nano. 16(5). 7242–7257. 57 indexed citations
3.
Zhang, Zhicheng, et al.. (2022). The miRNA-21-5p Payload in Exosomes from M2 Macrophages Drives Tumor Cell Aggression via PTEN/Akt Signaling in Renal Cell Carcinoma. International Journal of Molecular Sciences. 23(6). 3005–3005. 35 indexed citations
4.
Sharrow, Allison C., et al.. (2020). Using the Chicken Chorioallantoic Membrane In Vivo Model to Study Gynecological and Urological Cancers. Journal of Visualized Experiments. 11 indexed citations
5.
Sharrow, Allison C., et al.. (2020). Using the Chicken Chorioallantoic Membrane In Vivo Model to Study Gynecological and Urological Cancers. Journal of Visualized Experiments. 2 indexed citations
6.
Hu, Junhui, Shiruyeh Schokrpur, Maani M. Archang, et al.. (2018). A Non-integrating Lentiviral Approach Overcomes Cas9-Induced Immune Rejection to Establish an Immunocompetent Metastatic Renal Cancer Model. Molecular Therapy — Methods & Clinical Development. 9. 203–210. 31 indexed citations
7.
Hu, Junhui, Wei Guan, Peijun Liu, et al.. (2017). Endoglin Is Essential for the Maintenance of Self-Renewal and Chemoresistance in Renal Cancer Stem Cells. Stem Cell Reports. 9(2). 464–477. 45 indexed citations
8.
Sharrow, Allison C., Brandy Perkins, Michael I. Collector, et al.. (2016). Characterization of aldehyde dehydrogenase 1 high ovarian cancer cells: Towards targeted stem cell therapy. Gynecologic Oncology. 142(2). 341–348. 33 indexed citations
9.
Sharrow, Allison C., Brigitte M. Ronnett, Christopher J. Thoburn, et al.. (2010). Identification and characterization of a spontaneous ovarian carcinoma in Lewis rats. Journal of Ovarian Research. 3(1). 9–9. 5 indexed citations
10.
Robinson, Lisa, Irina L. Tourkova, Yujuan Wang, et al.. (2010). FSH-receptor isoforms and FSH-dependent gene transcription in human monocytes and osteoclasts. Biochemical and Biophysical Research Communications. 394(1). 12–17. 107 indexed citations
11.
Sharrow, Allison C., Yanan Li, Amanda Micsenyi, et al.. (2007). Modulation of osteoblast gap junction connectivity by serum, TNFα, and TRAIL. Experimental Cell Research. 314(2). 297–308. 27 indexed citations
12.
Yaroslavskiy, Beatrice B., Allison C. Sharrow, Alan Wells, Lisa Robinson, & Harry C. Blair. (2007). Necessity of inositol (1,4,5)-trisphosphate receptor 1 and μ-calpain in NO-induced osteoclast motility. Journal of Cell Science. 120(16). 2884–2894. 25 indexed citations
13.
Borysenko, Christopher W., Yanan Li, Anand Krishnan V. Iyer, et al.. (2006). Death receptor‐3 mediates apoptosis in human osteoblasts under narrowly regulated conditions. Journal of Cellular Physiology. 209(3). 1021–1028. 24 indexed citations
14.
Sun, Li, Yuanzhen Peng, Allison C. Sharrow, et al.. (2006). FSH Directly Regulates Bone Mass. Cell. 125(2). 247–260. 540 indexed citations breakdown →
15.
Yaroslavskiy, Beatrice B., Yongjun Zhang, Sara E. Kalla, et al.. (2005). NO-dependent osteoclast motility: reliance on cGMP-dependent protein kinase I and VASP. Journal of Cell Science. 118(23). 5479–5487. 42 indexed citations
16.
Frattini, Annalisa, Harry C. Blair, Maria Grazia Sacco, et al.. (2005). Rescue of ATPa3-deficient murine malignant osteopetrosis by hematopoietic stem cell transplantation in utero. Proceedings of the National Academy of Sciences. 102(41). 14629–14634. 42 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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