Z. Dave Sharp

9.6k total citations · 4 hit papers
68 papers, 7.3k citations indexed

About

Z. Dave Sharp is a scholar working on Molecular Biology, Genetics and Aging. According to data from OpenAlex, Z. Dave Sharp has authored 68 papers receiving a total of 7.3k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Molecular Biology, 18 papers in Genetics and 16 papers in Aging. Recurrent topics in Z. Dave Sharp's work include Genetics, Aging, and Longevity in Model Organisms (16 papers), Genomics and Chromatin Dynamics (13 papers) and Growth Hormone and Insulin-like Growth Factors (12 papers). Z. Dave Sharp is often cited by papers focused on Genetics, Aging, and Longevity in Model Organisms (16 papers), Genomics and Chromatin Dynamics (13 papers) and Growth Hormone and Insulin-like Growth Factors (12 papers). Z. Dave Sharp collaborates with scholars based in United States, Canada and Czechia. Z. Dave Sharp's co-authors include Randy Strong, Martin A. Javors, James F. Nelson, Richard A. Miller, Nancy L. Nadon, Elizabeth Fernández, Kevin Flurkey, Clinton M. Astle, John E. Wilkinson and Phang‐Lang Chen and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Z. Dave Sharp

68 papers receiving 7.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Rapamycin fed late in life extends lifespan in genetically heterogeneous mice

2009 2.8k citations Randy Strong, Z. Dave Sharp et al. profile →
Rapamycin, But Not Resveratrol or Simvastatin, Extends Life Span of Genetically Heterogeneous Mice

2010 686 citations Richard A. Miller, Clinton M. Astle et al. The Journals of Gerontology Series A profile →
Association of BRCA1 with the hRad50-hMre11-p95 Complex and the DNA Damage Response

1999 513 citations Chi‐Fen Chen, Shang Li et al. profile →
A general method for polyethylene-glycol-induced genetic transformation of bacteria and yeast

1983 410 citations Robert J. Klebe, June V. Harriss et al. Gene profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Z. Dave Sharp United States	27	4.4k	2.2k	1.9k	1.2k	708	68	7.3k
Clinton M. Astle United States	34	3.2k 0.7×	2.7k 1.2×	2.6k 1.4×	439 0.4×	879 1.2×	57	7.6k
Kevin Flurkey United States	29	2.9k 0.7×	3.1k 1.4×	2.9k 1.6×	527 0.4×	996 1.4×	57	7.0k
Terry G. Unterman United States	62	7.3k 1.6×	874 0.4×	2.5k 1.3×	1.2k 1.0×	498 0.7×	157	12.6k
Tadahiro Kitamura Japan	48	6.5k 1.5×	654 0.3×	2.5k 1.3×	1.4k 1.2×	791 1.1×	130	9.9k
Grant D. Barish United States	36	3.7k 0.8×	355 0.2×	2.3k 1.2×	731 0.6×	1.5k 2.1×	54	7.5k
Malene Hansen United States	39	4.7k 1.1×	3.5k 1.6×	1.9k 1.0×	276 0.2×	1.0k 1.5×	61	9.8k
Jay H. Chung United States	34	5.1k 1.1×	258 0.1×	1.5k 0.8×	961 0.8×	479 0.7×	73	7.7k
Fátima Bosch Spain	50	3.8k 0.9×	348 0.2×	2.4k 1.3×	1.8k 1.6×	262 0.4×	167	7.8k
Cole M. Haynes United States	40	7.1k 1.6×	2.1k 1.0×	2.1k 1.1×	251 0.2×	318 0.4×	66	10.1k
Seung‐Hoi Koo South Korea	44	6.2k 1.4×	219 0.1×	2.0k 1.1×	641 0.5×	329 0.5×	96	9.6k

Countries citing papers authored by Z. Dave Sharp

Since Specialization

Citations

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

Fields of papers citing papers by Z. Dave Sharp

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Z. Dave Sharp. 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 Z. Dave Sharp. The network helps show where Z. Dave Sharp may publish in the future.

Co-authorship network of co-authors of Z. Dave Sharp

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

All Works

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20 of 20 papers shown

Sharp, Z. Dave & Randy Strong. (2023). Rapamycin, the only drug that has been consistently demonstrated to increase mammalian longevity. An update. Experimental Gerontology. 176. 112166–112166. 22 indexed citations

Svatek, Robert S., Niannian Ji, Neelam Mukherjee, et al.. (2018). Rapamycin Prevents Surgery-Induced Immune Dysfunction in Patients with Bladder Cancer. Cancer Immunology Research. 7(3). 466–475. 20 indexed citations

Dao, Vinh, Srilakshmi Pandeswara, Vincent Hurez, et al.. (2015). Prevention of Carcinogen and Inflammation-Induced Dermal Cancer by Oral Rapamycin Includes Reducing Genetic Damage. Cancer Prevention Research. 8(5). 400–409. 16 indexed citations

Hurez, Vincent, Vinh Dao, Aijie Liu, et al.. (2015). Chronic mTOR inhibition in mice with rapamycin alters T , B , myeloid, and innate lymphoid cells and gut flora and prolongs life of immune‐deficient mice. Aging Cell. 14(6). 945–956. 98 indexed citations

Wang, Eunice S., et al.. (2015). Spatiotemporal control of estrogen-responsive transcription in ERα-positive breast cancer cells. Oncogene. 35(18). 2379–2389. 12 indexed citations

Miller, Richard A., David E. Harrison, Clinton M. Astle, et al.. (2013). Rapamycin‐mediated lifespan increase in mice is dose and sex dependent and metabolically distinct from dietary restriction. Aging Cell. 13(3). 468–477. 430 indexed citations

Hasty, Paul, Carolina B. Livi, Sherry G. Dodds, et al.. (2013). eRapa Restores a Normal Life Span in a FAP Mouse Model. Cancer Prevention Research. 7(1). 169–178. 56 indexed citations

Sharp, Z. Dave & Randy Strong. (2010). The Role of mTOR Signaling in Controlling Mammalian Life Span: What a Fungicide Teaches Us About Longevity. The Journals of Gerontology Series A. 65A(6). 580–589. 40 indexed citations

Miller, Richard A., Clinton M. Astle, Joseph A. Baur, et al.. (2010). Rapamycin, But Not Resveratrol or Simvastatin, Extends Life Span of Genetically Heterogeneous Mice. The Journals of Gerontology Series A. 66A(2). 191–201. 686 indexed citations breakdown →

10.

Garcı́a-Becerra, Rocio, Valeria Berno, David Ordaz‐Rosado, et al.. (2010). Ligand-induced large-scale chromatin dynamics as a biosensor for the detection of estrogen receptor subtype selective ligands. Gene. 458(1-2). 37–44. 5 indexed citations

11.

Berno, Valeria, Larbi Amazit, Cruz A. Hinojos, et al.. (2008). Activation of Estrogen Receptor-α by E2 or EGF Induces Temporally Distinct Patterns of Large-Scale Chromatin Modification and mRNA Transcription. PLoS ONE. 3(5). e2286–e2286. 26 indexed citations

12.

Nadon, Nancy L., Randy Strong, Richard A. Miller, et al.. (2008). Design of aging intervention studies: the NIA interventions testing program. AGE. 30(4). 187–199. 110 indexed citations

13.

Sharp, Z. Dave, Maureen G. Mancini, Cruz A. Hinojos, et al.. (2006). Estrogen-receptor-α exchange and chromatin dynamics are ligand- and domain-dependent. Journal of Cell Science. 119(19). 4101–4116. 92 indexed citations

14.

Sharp, Z. Dave, David L. Stenoien, Maureen G. Mancini, Ilia I. Ouspenski, & Michael A. Mancini. (2004). Inactivating Pit‐1 mutations alter subnuclear dynamics suggesting a protein misfolding and nuclear stress response. Journal of Cellular Biochemistry. 92(4). 664–678. 8 indexed citations

15.

Mancini, Maureen G., Bing Liu, Z. Dave Sharp, & Michael A. Mancini. (1999). Subnuclear partitioning and functional regulation of the Pit-1 transcription factor. Journal of Cellular Biochemistry. 72(3). 322–338. 44 indexed citations

16.

Morgan, W. W., Arlan Richardson, Z. Dave Sharp, & Christi A. Walter. (1999). Application of Exogenously Regulatable Promoter Systems to Transgenic Models for the Study of Aging. The Journals of Gerontology Series A. 54(1). B30–B40. 17 indexed citations

17.

Stenoien, David L., Z. Dave Sharp, Carolyn L. Smith, & Michael A. Mancini. (1998). Functional subnuclear partitioning of transcription factors. Journal of Cellular Biochemistry. 70(2). 213–221. 46 indexed citations

18.

Chen, Chi‐Fen, Shang Li, Yumay Chen, et al.. (1996). The Nuclear Localization Sequences of the BRCA1 Protein Interact with the Importin-α Subunit of the Nuclear Transport Signal Receptor. Journal of Biological Chemistry. 271(51). 32863–32868. 165 indexed citations

19.

Sharp, Z. Dave, et al.. (1989). DNA recognition element required for PUF-I mediated cell-type-specific transcription of the rat prolactin gene. Nucleic Acids Research. 17(7). 2705–2722. 16 indexed citations

20.

Klebe, Robert J., June V. Harriss, Z. Dave Sharp, & Michael G. Douglas. (1983). A general method for polyethylene-glycol-induced genetic transformation of bacteria and yeast. Gene. 25(2-3). 333–341. 410 indexed citations breakdown →

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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