H. Earl Ruley

11.8k total citations · 4 hit papers
74 papers, 10.1k citations indexed

About

H. Earl Ruley is a scholar working on Molecular Biology, Genetics and Oncology. According to data from OpenAlex, H. Earl Ruley has authored 74 papers receiving a total of 10.1k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Molecular Biology, 36 papers in Genetics and 17 papers in Oncology. Recurrent topics in H. Earl Ruley's work include Virus-based gene therapy research (24 papers), CRISPR and Genetic Engineering (15 papers) and Cancer-related Molecular Pathways (10 papers). H. Earl Ruley is often cited by papers focused on Virus-based gene therapy research (24 papers), CRISPR and Genetic Engineering (15 papers) and Cancer-related Molecular Pathways (10 papers). H. Earl Ruley collaborates with scholars based in United States, South Korea and United Kingdom. H. Earl Ruley's co-authors include Scott W. Lowe, Tyler Jacks, David E. Housman, S. W. Lowe, Stephan Bodis, Andrea I. McClatchey, Lee Ann Remington, David E. Fisher, Jin Chen and Geoffrey G. Hicks and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

H. Earl Ruley

74 papers receiving 9.7k citations

Hit Papers

p53-dependent apoptosis m... 1983 2026 1997 2011 1993 1994 1983 1993 500 1000 1.5k 2.0k 2.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
H. Earl Ruley United States 40 6.3k 4.5k 2.4k 1.1k 1.1k 74 10.1k
Charles A. Montgomery United States 24 5.8k 0.9× 4.3k 1.0× 1.9k 0.8× 1.3k 1.1× 957 0.9× 55 10.3k
Mourad Kaghad France 34 7.3k 1.2× 5.2k 1.2× 888 0.4× 948 0.8× 1.8k 1.6× 48 11.5k
Mark J. McArthur United States 26 4.3k 0.7× 3.6k 0.8× 746 0.3× 1.2k 1.0× 930 0.9× 45 6.9k
Manfred Gossen Germany 37 9.5k 1.5× 2.5k 0.6× 4.2k 1.7× 647 0.6× 558 0.5× 90 12.5k
Han‐Woong Lee South Korea 37 6.5k 1.0× 2.9k 0.6× 887 0.4× 884 0.8× 744 0.7× 112 11.5k
Yoji Ikawa Japan 48 7.2k 1.1× 2.3k 0.5× 1.6k 0.6× 973 0.8× 540 0.5× 221 11.9k
Arthur D. Levinson United States 52 8.9k 1.4× 3.7k 0.8× 2.8k 1.2× 1.2k 1.1× 317 0.3× 81 13.8k
Pedro R. Löwenstein United States 58 5.4k 0.8× 2.2k 0.5× 3.5k 1.4× 802 0.7× 459 0.4× 304 11.1k
Eisuke Mekada Japan 48 4.2k 0.7× 2.0k 0.4× 624 0.3× 676 0.6× 908 0.8× 130 8.4k
Nicholas C. Dracopoli United States 37 4.2k 0.7× 2.8k 0.6× 1.9k 0.8× 1.6k 1.4× 134 0.1× 88 7.6k

Countries citing papers authored by H. Earl Ruley

Since Specialization
Citations

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

Fields of papers citing papers by H. Earl Ruley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by H. Earl Ruley. 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 H. Earl Ruley. The network helps show where H. Earl Ruley may publish in the future.

Co-authorship network of co-authors of H. Earl Ruley

This figure shows the co-authorship network connecting the top 25 collaborators of H. Earl Ruley. A scholar is included among the top collaborators of H. Earl Ruley 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 H. Earl Ruley. H. Earl Ruley 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.
Duong, Tam, Jaetaek Kim, H. Earl Ruley, & Daewoong Jo. (2014). Cell-Permeable Parkin Proteins Suppress Parkinson Disease-Associated Phenotypes in Cultured Cells and Animals. PLoS ONE. 9(7). e102517–e102517. 6 indexed citations
2.
Lim, Junghee, Tam Duong, Baik Lin Seong, et al.. (2013). The effect of intracellular protein delivery on the anti-tumor activity of recombinant human endostatin. Biomaterials. 34(26). 6261–6271. 15 indexed citations
3.
Lim, Junghee, Tam Duong, Jaetaek Kim, et al.. (2012). Antitumor Activity of Cell-Permeable RUNX3 Protein in Gastric Cancer Cells. Clinical Cancer Research. 19(3). 680–690. 13 indexed citations
4.
Lim, Junghee, Jungeun Kim, Tam Duong, et al.. (2012). Antitumor Activity of Cell-Permeable p18INK4c With Enhanced Membrane and Tissue Penetration. Molecular Therapy. 20(8). 1540–1549. 13 indexed citations
5.
Carlesso, Gianluca, Anna B. Osipovich, Qing Lin, et al.. (2008). Subunit 1 of the Prefoldin Chaperone Complex Is Required for Lymphocyte Development and Function. The Journal of Immunology. 181(1). 476–484. 31 indexed citations
6.
Lin, Qing, et al.. (2006). Mutagenesis of diploid mammalian genes by gene entrapment. Nucleic Acids Research. 34(20). e139–e139. 10 indexed citations
7.
Osipovich, Anna B., Aparna Singh, & H. Earl Ruley. (2005). Post-entrapment genome engineering: First exon size does not affect the expression of fusion transcripts generated by gene entrapment. Genome Research. 15(3). 428–435. 14 indexed citations
8.
Sheng, Jinsong, et al.. (2004). Mutations in the IGF-II pathway that confer resistance to lytic reovirus infection. BMC Cell Biology. 5(1). 32–32. 15 indexed citations
9.
Sheng, Jinsong, et al.. (2004). Discovery of mammalian genes that participate in virus infection. BMC Cell Biology. 5(1). 41–41. 15 indexed citations
11.
Bendall, Heather, Geoffrey G. Hicks, Abudi Nashabi, et al.. (2003). The High-Mobility-Group Box Protein SSRP1/T160 Is Essential for Cell Viability in Day 3.5 Mouse Embryos. Molecular and Cellular Biology. 23(15). 5301–5307. 55 indexed citations
12.
Williamson, Douglas J., et al.. (2000). hnRNP C Is Required for Postimplantation Mouse Development but Is Dispensable for Cell Viability. Molecular and Cellular Biology. 20(11). 4094–4105. 54 indexed citations
13.
Ruley, H. Earl, et al.. (2000). Ly108: a new member of the mouse CD2 family of cell surface proteins. Immunogenetics. 52(1-2). 63–72. 42 indexed citations
14.
Hicks, Geoffrey G., Nagendra Singh, Abudi Nashabi, et al.. (2000). Fus deficiency in mice results in defective B-lymphocyte development and activation, high levels of chromosomal instability and perinatal death. Nature Genetics. 24(2). 175–179. 231 indexed citations
15.
DeGregori, James, Harald von Melchner, Helen Rayburn, et al.. (1994). A murine homolog of the yeast RNA1 gene is required for postimplantation development.. Genes & Development. 8(3). 265–276. 87 indexed citations
16.
Kuo, Alfred C., et al.. (1991). Mechanisms of oncogene cooperation: activation and inactivation of a growth antagonist.. Environmental Health Perspectives. 93. 97–103. 6 indexed citations
17.
Melchner, Harald von & H. Earl Ruley. (1990). Retroviruses as genetic tools to isolate transcriptionally active chromosomal regions.. Environmental Health Perspectives. 88. 141–148. 1 indexed citations
18.
Whyte, Peter, H. Earl Ruley, & Ed Harlow. (1988). Two regions of the adenovirus early region 1A proteins are required for transformation. Journal of Virology. 62(1). 257–265. 213 indexed citations
19.
Ruley, H. Earl, et al.. (1988). The Structure and Function of the Integrated Polyoma Virus DNA in 82-Rat and 53-Rat Transformed Cells. Journal of General Virology. 69(1). 197–207. 1 indexed citations
20.
Ruley, H. Earl & Michael G. Fried. (1983). Sequence repeats in a polyoma virus DNA region important for gene expression. Journal of Virology. 47(1). 233–237. 68 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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