Daniel G. Miller

5.9k total citations · 2 hit papers
34 papers, 3.9k citations indexed

About

Daniel G. Miller is a scholar working on Molecular Biology, Genetics and Genetics. According to data from OpenAlex, Daniel G. Miller has authored 34 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Molecular Biology, 19 papers in Genetics and 6 papers in Genetics. Recurrent topics in Daniel G. Miller's work include Virus-based gene therapy research (16 papers), Muscle Physiology and Disorders (14 papers) and RNA Interference and Gene Delivery (10 papers). Daniel G. Miller is often cited by papers focused on Virus-based gene therapy research (16 papers), Muscle Physiology and Disorders (14 papers) and RNA Interference and Gene Delivery (10 papers). Daniel G. Miller collaborates with scholars based in United States, Netherlands and Germany. Daniel G. Miller's co-authors include David W. Russell, Lisa M. Petek, Rabi Tawil, Silvère M. van der Maarel, James M. Allen, Stephen J. Tapscott, Mark S. Sands, Lauren Snider, Richard J.L.F. Lemmers and Anthony Donsante and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nature Medicine.

In The Last Decade

Daniel G. Miller

34 papers receiving 3.8k citations

Hit Papers

A Unifying Genetic Model for Facioscapulohumeral Muscular... 2004 2026 2011 2018 2010 2004 100 200 300 400 500

Peers

Daniel G. Miller
Yongping Yue United States
Christian Hinderer United States
Cathryn Mah United States
R. Jude Samulski United States
Joshua C. Grieger United States
Leszek Lisowski Australia
Larry A. Couture United States
Yongping Yue United States
Daniel G. Miller
Citations per year, relative to Daniel G. Miller Daniel G. Miller (= 1×) peers Yongping Yue

Countries citing papers authored by Daniel G. Miller

Since Specialization
Citations

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

Fields of papers citing papers by Daniel G. Miller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel G. Miller. 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 Daniel G. Miller. The network helps show where Daniel G. Miller may publish in the future.

Co-authorship network of co-authors of Daniel G. Miller

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel G. Miller. A scholar is included among the top collaborators of Daniel G. Miller 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 Daniel G. Miller. Daniel G. Miller 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.
Genereux, Diane P., Jamie M. Goodson, Noah Simon, et al.. (2017). Epigenetic memory via concordant DNA methylation is inversely correlated to developmental potential of mammalian cells. PLoS Genetics. 13(11). e1007060–e1007060. 13 indexed citations
3.
Petek, Lisa M., et al.. (2015). Endogenous DUX4 expression in FSHD myotubes is sufficient to cause cell death and disrupts RNA splicing and cell migration pathways. Human Molecular Genetics. 24(20). 5901–5914. 143 indexed citations
4.
Adair, Jennifer E., Brian C. Beard, David J. Rawlings, et al.. (2015). VISA - Vector Integration Site Analysis server: a web-based server to rapidly identify retroviral integration sites from next-generation sequencing. BMC Bioinformatics. 16(1). 212–212. 38 indexed citations
5.
Rensburg, Ruan van, Ines Beyer, Oleg Denisenko, et al.. (2012). Chromatin structure of two genomic sites for targeted transgene integration in induced pluripotent stem cells and hematopoietic stem cells. Gene Therapy. 20(2). 201–214. 35 indexed citations
6.
Block, Gregory J., Lisa M. Petek, James M. Moore, et al.. (2012). Asymmetric Bidirectional Transcription from the FSHD-Causing D4Z4 Array Modulates DUX4 Production. PLoS ONE. 7(4). e35532–e35532. 21 indexed citations
7.
Maarel, Silvère M. van der, Daniel G. Miller, Rabi Tawil, Galina N. Filippova, & Stephen J. Tapscott. (2012). Facioscapulohumeral muscular dystrophy. Current Opinion in Neurology. 25(5). 614–620. 35 indexed citations
8.
Miller, Daniel G., Josep Maria Casasa i Carbo, Gregory J. Block, et al.. (2011). Epigenetic regulation of the X-chromosomal macrosatellite repeat encoding for the cancer/testis gene CT47. European Journal of Human Genetics. 20(2). 185–191. 10 indexed citations
9.
Miller, Daniel G.. (2011). AAV-Mediated Gene Targeting. Methods in molecular biology. 807. 301–315. 7 indexed citations
10.
Lemmers, Richard J.L.F., Patrick J. van der Vliet, Rinse Klooster, et al.. (2010). A Unifying Genetic Model for Facioscapulohumeral Muscular Dystrophy. Science. 329(5999). 1650–1653. 528 indexed citations breakdown →
11.
Stadler, Bradford, Irena L. Ivanovska, Kshama Mehta, et al.. (2010). Characterization of microRNAs Involved in Embryonic Stem Cell States. Stem Cells and Development. 19(7). 935–950. 123 indexed citations
12.
Petek, Lisa M., Philip Fleckman, & Daniel G. Miller. (2010). Efficient KRT14 Targeting and Functional Characterization of Transplanted Human Keratinocytes for the Treatment of Epidermolysis Bullosa Simplex. Molecular Therapy. 18(9). 1624–1632. 33 indexed citations
13.
Snider, Lauren, Linda N. Geng, Richard J.L.F. Lemmers, et al.. (2010). Facioscapulohumeral Dystrophy: Incomplete Suppression of a Retrotransposed Gene. PLoS Genetics. 6(10). e1001181–e1001181. 364 indexed citations
14.
Snider, Lauren, Ashlee E. Tyler, Linda N. Geng, et al.. (2009). RNA transcripts, miRNA-sized fragments and proteins produced from D4Z4 units: new candidates for the pathophysiology of facioscapulohumeral dystrophy. Human Molecular Genetics. 18(13). 2414–2430. 167 indexed citations
15.
Beard, Brian C., David Dickerson, James Fletcher, et al.. (2007). Comparison of HIV-derived Lentiviral and MLV-based Gammaretroviral Vector Integration Sites in Primate Repopulating Cells. Molecular Therapy. 15(7). 1356–1365. 90 indexed citations
16.
Miller, Daniel G., Pei-Rong Wang, Lisa M. Petek, et al.. (2006). Gene targeting in vivo by adeno-associated virus vectors. Nature Biotechnology. 24(8). 1022–1026. 72 indexed citations
17.
Aker, Mari, Julie Tubb, Daniel G. Miller, George Stamatoyannopoulos, & David W. Emery. (2006). Integration Bias of Gammaretrovirus Vectors following Transduction and Growth of Primary Mouse Hematopoietic Progenitor Cells with and without Selection. Molecular Therapy. 14(2). 226–235. 12 indexed citations
18.
Hirata, Roli K., Cong Xu, Rong Dong, et al.. (2004). Efficient PRNP Gene Targeting in Bovine Fibroblasts by Adeno-Associated Virus Vectors. Cloning and Stem Cells. 6(1). 31–36. 14 indexed citations
19.
Miller, Daniel G., Lisa M. Petek, & David W. Russell. (2003). Human Gene Targeting by Adeno-Associated Virus Vectors Is Enhanced by DNA Double-Strand Breaks. Molecular and Cellular Biology. 23(10). 3550–3557. 98 indexed citations
20.
Miller, Daniel G., Elizabeth A. Rutledge, & David W. Russell. (2002). Chromosomal effects of adeno-associated virus vector integration. Nature Genetics. 30(2). 147–148. 122 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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