Pedro Miura

4.4k total citations · 1 hit paper
39 papers, 3.2k citations indexed

About

Pedro Miura is a scholar working on Molecular Biology, Cancer Research and Cellular and Molecular Neuroscience. According to data from OpenAlex, Pedro Miura has authored 39 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Molecular Biology, 12 papers in Cancer Research and 8 papers in Cellular and Molecular Neuroscience. Recurrent topics in Pedro Miura's work include RNA Research and Splicing (17 papers), Muscle Physiology and Disorders (11 papers) and RNA modifications and cancer (10 papers). Pedro Miura is often cited by papers focused on RNA Research and Splicing (17 papers), Muscle Physiology and Disorders (11 papers) and RNA modifications and cancer (10 papers). Pedro Miura collaborates with scholars based in United States, Canada and United Kingdom. Pedro Miura's co-authors include Mariela Cortés-López, Eric C. Lai, Sol Shenker, Jakub Orzechowski Westholm, Piero Sanfilippo, Daphne Cooper, Bernard J. Jasmin, S Celniker, Brenton R. Graveley and Brian Joseph and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Pedro Miura

39 papers receiving 3.2k citations

Hit Papers

Genome-wide Analysis of Drosophila Circular RNAs Reveals ... 2014 2026 2018 2022 2014 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pedro Miura United States 26 3.0k 1.5k 299 263 229 39 3.2k
Mingyan Lin United States 23 1.6k 0.5× 567 0.4× 62 0.2× 126 0.5× 121 0.5× 38 2.1k
Yuning Wei China 10 1.3k 0.4× 882 0.6× 107 0.4× 62 0.2× 61 0.3× 15 1.7k
Fumiaki Saito Japan 22 2.3k 0.8× 218 0.1× 471 1.6× 644 2.4× 864 3.8× 54 3.0k
Jakob S. Satz United States 15 1.8k 0.6× 139 0.1× 299 1.0× 471 1.8× 505 2.2× 16 2.2k
Zhengliang Gao China 15 1.1k 0.4× 412 0.3× 107 0.4× 85 0.3× 252 1.1× 46 1.7k
Iain W. McKinnell United Kingdom 22 1.7k 0.6× 132 0.1× 327 1.1× 344 1.3× 231 1.0× 29 2.1k
Jean‐Philippe Hugnot France 28 2.6k 0.9× 295 0.2× 189 0.6× 128 0.5× 655 2.9× 62 3.4k
Peggy Janich Germany 21 1.1k 0.4× 277 0.2× 273 0.9× 235 0.9× 119 0.5× 24 1.9k
Rajini Srinivasan United States 22 1.4k 0.5× 246 0.2× 75 0.3× 157 0.6× 437 1.9× 26 2.0k
Scott Q. Harper United States 27 3.9k 1.3× 612 0.4× 282 0.9× 231 0.9× 1.1k 4.8× 54 4.4k

Countries citing papers authored by Pedro Miura

Since Specialization
Citations

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

Fields of papers citing papers by Pedro Miura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pedro Miura

This figure shows the co-authorship network connecting the top 25 collaborators of Pedro Miura. A scholar is included among the top collaborators of Pedro Miura 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 Pedro Miura. Pedro Miura 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.
So, Kevin Kam Fung, Joshua G. Harrison, Zachariah Gompert, et al.. (2025). High Quality Diet Enhances Immune Response and Affects Gene Expression During Viral Infection in an Insect Herbivore. Molecular Ecology. 34(15). e17694–e17694. 1 indexed citations
2.
Zhang, Zhiping, et al.. (2023). Coordination of alternative splicing and alternative polyadenylation revealed by targeted long read sequencing. Nature Communications. 14(1). 5506–5506. 20 indexed citations
4.
Cooper, Daphne, et al.. (2021). NOVA2 regulates neural circRNA biogenesis. Nucleic Acids Research. 49(12). 6849–6862. 58 indexed citations
5.
Miura, Pedro, et al.. (2021). CRISPR-Mediated Knockout of Long 3′ UTR mRNA Isoforms in mESC-Derived Neurons. Frontiers in Genetics. 12. 789434–789434. 3 indexed citations
6.
Miura, Pedro, et al.. (2020). Emerging Roles for 3′ UTRs in Neurons. International Journal of Molecular Sciences. 21(10). 3413–3413. 55 indexed citations
7.
Cooper, Daphne, Mariela Cortés-López, & Pedro Miura. (2018). Genome-Wide circRNA Profiling from RNA-seq Data. Methods in molecular biology. 1724. 27–41. 30 indexed citations
8.
Miura, Pedro, et al.. (2018). CircRNA accumulation: A new hallmark of aging?. Mechanisms of Ageing and Development. 173. 71–79. 65 indexed citations
9.
Miura, Pedro, et al.. (2018). Age-related defects in short-term plasticity are reversed by acetyl-L-carnitine at the mouse calyx of Held. Neurobiology of Aging. 67. 108–119. 4 indexed citations
10.
Liu, Wenxuan, Alanna Klose, Nicole D. Paris, et al.. (2017). Loss of adult skeletal muscle stem cells drives age-related neuromuscular junction degeneration. eLife. 6. 140 indexed citations
11.
Sanfilippo, Piero, Pedro Miura, & Eric C. Lai. (2017). Genome-wide profiling of the 3' ends of polyadenylated RNAs. Methods. 126. 86–94. 17 indexed citations
12.
Gruner, Hannah N., Mariela Cortés-López, Daphne Cooper, Matthew Bauer, & Pedro Miura. (2016). CircRNA accumulation in the aging mouse brain. Scientific Reports. 6(1). 38907–38907. 272 indexed citations
13.
Westholm, Jakub Orzechowski, Pedro Miura, Sara Olson, et al.. (2014). Genome-wide Analysis of Drosophila Circular RNAs Reveals Their Structural and Sequence Properties and Age-Dependent Neural Accumulation. Cell Reports. 9(5). 1966–1980. 774 indexed citations breakdown →
14.
Shenker, Sol, Pedro Miura, Piero Sanfilippo, & Eric C. Lai. (2014). IsoSCM: improved and alternative 3′ UTR annotation using multiple change-point inference. RNA. 21(1). 14–27. 46 indexed citations
15.
Miura, Pedro, Sol Shenker, Celia Andreu-Agulló, Jakub Orzechowski Westholm, & Eric C. Lai. (2013). Widespread and extensive lengthening of 3′ UTRs in the mammalian brain. Genome Research. 23(5). 812–825. 251 indexed citations
16.
Miura, Pedro, et al.. (2010). The utrophin A 5'-UTR drives cap-independent translation exclusively in skeletal muscles of transgenic mice and interacts with eEF1A2. Human Molecular Genetics. 19(7). 1211–1220. 32 indexed citations
17.
Chakkalakal, Joe V., et al.. (2007). Modulation of utrophin A mRNA stability in fast versus slow muscles via an AU-rich element and calcineurin signaling. Nucleic Acids Research. 36(3). 826–838. 44 indexed citations
18.
Miura, Pedro & Bernard J. Jasmin. (2006). Utrophin upregulation for treating Duchenne or Becker muscular dystrophy: how close are we?. Trends in Molecular Medicine. 12(3). 122–129. 89 indexed citations
19.
Miura, Pedro, Jennifer Thompson, Joe V. Chakkalakal, Martin Holčı́k, & Bernard J. Jasmin. (2005). The Utrophin A 5′-Untranslated Region Confers Internal Ribosome Entry Site-mediated Translational Control during Regeneration of Skeletal Muscle Fibers. Journal of Biological Chemistry. 280(38). 32997–33005. 53 indexed citations
20.
Vaughan, Patricia S., Pedro Miura, Matthew Henderson, Belinda Byrne, & Kevin T. Vaughan. (2002). A role for regulated binding of p150 Glued to microtubule plus ends in organelle transport. The Journal of Cell Biology. 158(2). 305–319. 190 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026