David Mu

12.6k total citations · 5 hit papers
74 papers, 10.0k citations indexed

About

David Mu is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, David Mu has authored 74 papers receiving a total of 10.0k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Molecular Biology, 18 papers in Cancer Research and 13 papers in Oncology. Recurrent topics in David Mu's work include DNA Repair Mechanisms (19 papers), CRISPR and Genetic Engineering (14 papers) and RNA modifications and cancer (14 papers). David Mu is often cited by papers focused on DNA Repair Mechanisms (19 papers), CRISPR and Genetic Engineering (14 papers) and RNA modifications and cancer (14 papers). David Mu collaborates with scholars based in United States, Germany and Russia. David Mu's co-authors include Aziz Sancar, Scott W. Lowe, Scott Powers, Carlos Cordon‐Cardo, Gregory J. Hannon, J. Michael Thomson, Scott M. Hammond, Eva Hernando, Michael T. Hemann and Lin He and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

David Mu

66 papers receiving 9.8k citations

Hit Papers

A microRNA polycistron as a potential human oncogene 1990 2026 2002 2014 2005 2006 2007 1990 1995 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
David Mu United States 40 8.6k 3.9k 1.2k 778 624 74 10.0k
Nicholas Denko United States 44 6.5k 0.8× 5.0k 1.3× 1.5k 1.2× 1.4k 1.8× 411 0.7× 93 10.2k
Edurne Berra France 43 6.0k 0.7× 4.7k 1.2× 1.1k 0.9× 770 1.0× 401 0.6× 69 9.4k
Yang Wang China 45 8.1k 0.9× 3.8k 1.0× 793 0.7× 524 0.7× 149 0.2× 225 9.5k
Mircea Ivan United States 37 8.3k 1.0× 8.3k 2.2× 1.3k 1.1× 568 0.7× 441 0.7× 80 11.9k
Mridul Mukherji United States 21 6.2k 0.7× 5.5k 1.4× 753 0.6× 588 0.8× 554 0.9× 40 9.3k
Peppi Koivunen Finland 37 3.8k 0.4× 3.4k 0.9× 458 0.4× 577 0.7× 397 0.6× 101 6.3k
Michael Ohh Canada 44 7.7k 0.9× 6.9k 1.8× 1.7k 1.4× 853 1.1× 425 0.7× 99 11.2k
Diana Whitaker‐Menezes United States 49 6.1k 0.7× 4.6k 1.2× 2.0k 1.7× 1.2k 1.5× 202 0.3× 93 9.4k
Ya‐Min Tian United Kingdom 25 7.1k 0.8× 8.1k 2.1× 846 0.7× 652 0.8× 811 1.3× 32 11.2k
Ketan J. Patel United Kingdom 39 4.9k 0.6× 1.4k 0.4× 989 0.8× 637 0.8× 195 0.3× 58 6.0k

Countries citing papers authored by David Mu

Since Specialization
Citations

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

Fields of papers citing papers by David Mu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Mu

This figure shows the co-authorship network connecting the top 25 collaborators of David Mu. A scholar is included among the top collaborators of David Mu 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 David Mu. David Mu 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.
Kong, Yali, Michael Edler, Ernest Hamel, et al.. (2024). Synthesis and structure-activity relationship of boronic acid bioisosteres of combretastatin A-4 as anticancer agents. Bioorganic & Medicinal Chemistry. 116. 117999–117999. 3 indexed citations
2.
Mu, David, et al.. (2017). Roles of Thyroid Transcription Factor 1 in Lung Cancer Biology. Vitamins and hormones. 106. 517–544. 20 indexed citations
3.
Hudry, Eloïse, Sunil Gandhi, Bence György, et al.. (2016). Exosome-associated AAV vector as a robust and convenient neuroscience tool. Gene Therapy. 23(4). 380–392. 118 indexed citations
4.
Runkle, E. Aaron & David Mu. (2013). Tight junction proteins: From barrier to tumorigenesis. Cancer Letters. 337(1). 41–48. 174 indexed citations
5.
Rice, Shawn J., et al.. (2013). MicroRNA-33a Mediates the Regulation of High Mobility Group AT-Hook 2 Gene (HMGA2) by Thyroid Transcription Factor 1 (TTF-1/NKX2–1). Journal of Biological Chemistry. 288(23). 16348–16360. 52 indexed citations
6.
Conkrite, Karina L., et al.. (2012). Cooperation between Rb and Arf in suppressing mouse retinoblastoma. Journal of Clinical Investigation. 122(5). 1726–1733. 21 indexed citations
7.
Oliver, Trudy G., Kim L. Mercer, Leanne C. Sayles, et al.. (2010). Chronic cisplatin treatment promotes enhanced damage repair and tumor progression in a mouse model of lung cancer. Genes & Development. 24(8). 837–852. 7 indexed citations
8.
Wu, Rong, Rork Kuick, Scott Powers, et al.. (2008). Neurofibromin 1 (NF1) Defects Are Common in Human Ovarian Serous Carcinomas and Co-occur with TP53 Mutations. Neoplasia. 10(12). 1362–IN9. 65 indexed citations
9.
Connolly, James L., Andrew Siderowf, Christopher M. Clark, David Mu, & Domenico Praticò. (2008). F2 Isoprostane Levels in Plasma and Urine do not Support Increased Lipid Peroxidation in Cognitively Impaired Parkinson Disease Patients. Cognitive and Behavioral Neurology. 21(2). 83–86. 22 indexed citations
10.
Miao, Jiangyong, David Mu, Zhenfeng Duan, et al.. (2008). Hepsin colocalizes with desmosomes and induces progression of ovarian cancer in a mouse model. International Journal of Cancer. 123(9). 2041–2047. 37 indexed citations
11.
MacPherson, David, et al.. (2007). Murine bilateral retinoblastoma exhibiting rapid‐onset, metastatic progression and N‐myc gene amplification. The EMBO Journal. 26(3). 784–794. 54 indexed citations
12.
Scott, Clare L., Jesús Gil, Eva Hernando, et al.. (2007). Role of the chromobox protein CBX7 in lymphomagenesis. Proceedings of the National Academy of Sciences. 104(13). 5389–5394. 135 indexed citations
13.
Geurts, Aron M., Lara S. Collier, Jennifer L. Geurts, et al.. (2006). Gene Mutations and Genomic Rearrangements in the Mouse as a Result of Transposon Mobilization from Chromosomal Concatemers. PLoS Genetics. 2(9). e156–e156. 75 indexed citations
14.
Mu, David, Liyun Chen, Xiping Zhang, et al.. (2003). Genomic amplification and oncogenic properties of the KCNK9 potassium channel gene. Cancer Cell. 3(3). 297–302. 208 indexed citations
16.
Mu, David & Aziz Sancar. (1997). Model for XPC-independent Transcription-coupled Repair of Pyrimidine Dimers in Humans. Journal of Biological Chemistry. 272(12). 7570–7573. 81 indexed citations
17.
Mu, David & A Sancar. (1997). DNA Excision Repair Assays. Progress in nucleic acid research and molecular biology. 56. 63–81. 8 indexed citations
18.
Matsunaga, Tsukasa, Chi-Hyun Park, Tadayoshi Bessho, David Mu, & Aziz Sancar. (1996). Replication Protein A Confers Structure-specific Endonuclease Activities to the XPF-ERCC1 and XPG Subunits of Human DNA Repair Excision Nuclease. Journal of Biological Chemistry. 271(19). 11047–11050. 164 indexed citations
19.
Mu, David, et al.. (1995). Reconstitution of Human DNA Repair Excision Nuclease in a Highly Defined System. Journal of Biological Chemistry. 270(6). 2415–2418. 401 indexed citations breakdown →
20.
Mu, David & Judith P. Klinman. (1995). [8] Cloning of mammalian topa quinone-containing enzymes. Methods in enzymology on CD-ROM/Methods in enzymology. 258. 114–122. 1 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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