Matthew S. Wilken

5.2k total citations · 1 hit paper
17 papers, 1.9k citations indexed

About

Matthew S. Wilken is a scholar working on Molecular Biology, Developmental Neuroscience and Immunology. According to data from OpenAlex, Matthew S. Wilken has authored 17 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 5 papers in Developmental Neuroscience and 4 papers in Immunology. Recurrent topics in Matthew S. Wilken's work include Retinal Development and Disorders (9 papers), Neurogenesis and neuroplasticity mechanisms (5 papers) and CRISPR and Genetic Engineering (4 papers). Matthew S. Wilken is often cited by papers focused on Retinal Development and Disorders (9 papers), Neurogenesis and neuroplasticity mechanisms (5 papers) and CRISPR and Genetic Engineering (4 papers). Matthew S. Wilken collaborates with scholars based in United States, Greece and Germany. Matthew S. Wilken's co-authors include Thomas A. Reh, Kristin A. Hogquist, Tom M. McCaughtry, Nikolas L. Jorstad, Kristin E. Cox, Yumi Ueki, Rachel Wong, Fred Rieke, Leah S. VandenBosch and Stefanie G. Wohl and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Matthew S. Wilken

16 papers receiving 1.9k citations

Hit Papers

De novo design of protein logic gates 2020 2026 2022 2024 2020 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthew S. Wilken United States 16 1.3k 387 363 269 190 17 1.9k
Peter Stoilov United States 29 2.9k 2.2× 157 0.4× 372 1.0× 153 0.6× 31 0.2× 51 3.5k
Ellen J. Collarini United States 18 951 0.7× 155 0.4× 338 0.9× 582 2.2× 15 0.1× 38 1.7k
Yanaí Durán United Kingdom 24 2.5k 1.9× 146 0.4× 1.1k 3.0× 70 0.3× 792 4.2× 35 3.0k
Takayuki Kanaseki Japan 31 1.5k 1.1× 1.1k 2.9× 313 0.9× 25 0.1× 76 0.4× 142 3.1k
Arifa Naeem United Kingdom 14 981 0.7× 65 0.2× 619 1.7× 135 0.5× 127 0.7× 15 1.2k
Jen-Zen Chuang United States 20 1.8k 1.3× 128 0.3× 809 2.2× 91 0.3× 188 1.0× 32 2.3k
Ed Manser Singapore 29 1.7k 1.3× 199 0.5× 233 0.6× 56 0.2× 50 0.3× 43 2.6k
Ian J. White United Kingdom 22 1.2k 0.9× 328 0.8× 526 1.4× 183 0.7× 9 0.0× 40 2.2k
Sarah J. Heasman United Kingdom 9 1.2k 0.9× 359 0.9× 215 0.6× 54 0.2× 20 0.1× 10 2.1k
Fumiyoshi Ishidate Japan 15 946 0.7× 325 0.8× 177 0.5× 149 0.6× 7 0.0× 22 1.7k

Countries citing papers authored by Matthew S. Wilken

Since Specialization
Citations

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

Fields of papers citing papers by Matthew S. Wilken

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew S. Wilken. 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 Matthew S. Wilken. The network helps show where Matthew S. Wilken may publish in the future.

Co-authorship network of co-authors of Matthew S. Wilken

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

All Works

17 of 17 papers shown
1.
Psatha, Nikoletta, Pavel Sova, Grigorios Georgolopoulos, et al.. (2025). Large-scale discovery of potent, compact and erythroid specific enhancers for gene therapy vectors. Nature Communications. 16(1). 4325–4325.
2.
VandenBosch, Leah S., Stefanie G. Wohl, Matthew S. Wilken, et al.. (2020). Developmental changes in the accessible chromatin, transcriptome and Ascl1-binding correlate with the loss in Müller Glial regenerative potential. Scientific Reports. 10(1). 13615–13615. 25 indexed citations
3.
Chen, Zibo, Ryan D. Kibler, Andrew C. Hunt, et al.. (2020). De novo design of protein logic gates. Science. 368(6486). 78–84. 158 indexed citations breakdown →
4.
Jorstad, Nikolas L., Matthew S. Wilken, Levi Todd, et al.. (2020). STAT Signaling Modifies Ascl1 Chromatin Binding and Limits Neural Regeneration from Muller Glia in Adult Mouse Retina. Cell Reports. 30(7). 2195–2208.e5. 80 indexed citations
5.
Wilkerson, Brent A., Alex Chitsazan, Leah S. VandenBosch, et al.. (2019). Open chromatin dynamics in prosensory cells of the embryonic mouse cochlea. Scientific Reports. 9(1). 9060–9060. 15 indexed citations
6.
Jorstad, Nikolas L., Matthew S. Wilken, William N. Grimes, et al.. (2017). Stimulation of functional neuronal regeneration from Müller glia in adult mice. Nature. 548(7665). 103–107. 339 indexed citations
7.
Hoshino, Akina, Rinki Ratnapriya, Matthew J. Brooks, et al.. (2017). Molecular Anatomy of the Developing Human Retina. Developmental Cell. 43(6). 763–779.e4. 169 indexed citations
8.
Wilken, Matthew S. & Thomas A. Reh. (2016). Retinal regeneration in birds and mice. Current Opinion in Genetics & Development. 40. 57–64. 45 indexed citations
9.
Ueki, Yumi, Matthew S. Wilken, Kristin E. Cox, et al.. (2015). Transgenic expression of the proneural transcription factor Ascl1 in Müller glia stimulates retinal regeneration in young mice. Proceedings of the National Academy of Sciences. 112(44). 13717–13722. 180 indexed citations
10.
Wilken, Matthew S., Joseph A. Brzezinski, Anna La Torre, et al.. (2015). DNase I hypersensitivity analysis of the mouse brain and retina identifies region-specific regulatory elements. Epigenetics & Chromatin. 8(1). 8–8. 46 indexed citations
11.
Zhang, Jianmin, Russell J. Taylor, Anna La Torre, et al.. (2015). Ezh2 maintains retinal progenitor proliferation, transcriptional integrity, and the timing of late differentiation. Developmental Biology. 403(2). 128–138. 50 indexed citations
12.
Ueki, Yumi, Matthew S. Wilken, Kristin E. Cox, et al.. (2015). A transient wave of BMP signaling in the retina is necessary for Müller glial differentiation. Development. 142(3). 533–543. 27 indexed citations
13.
Pollak, Julia, Matthew S. Wilken, Yumi Ueki, et al.. (2013). ASCL1 reprograms mouse Müller glia into neurogenic retinal progenitors. Development. 140(12). 2619–2631. 182 indexed citations
14.
Ueki, Yumi, Michael Karl, Julia Pollak, et al.. (2012). P53 is required for the developmental restriction in Müller glial proliferation in mouse retina. Glia. 60(10). 1579–1589. 45 indexed citations
15.
Wu, Kailang, Guiqing Peng, Matthew S. Wilken, Robert J. Geraghty, & Fang Li. (2012). Mechanisms of Host Receptor Adaptation by Severe Acute Respiratory Syndrome Coronavirus. Journal of Biological Chemistry. 287(12). 8904–8911. 188 indexed citations
16.
McCaughtry, Tom M., Troy A. Baldwin, Matthew S. Wilken, & Kristin A. Hogquist. (2008). Clonal deletion of thymocytes can occur in the cortex with no involvement of the medulla. The Journal of Experimental Medicine. 205(11). 2575–2584. 146 indexed citations
17.
McCaughtry, Tom M., Matthew S. Wilken, & Kristin A. Hogquist. (2007). Thymic emigration revisited. The Journal of Experimental Medicine. 204(11). 2513–2520. 211 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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