Killian S. Hanlon

1.2k total citations · 1 hit paper
16 papers, 782 citations indexed

About

Killian S. Hanlon is a scholar working on Molecular Biology, Genetics and Sensory Systems. According to data from OpenAlex, Killian S. Hanlon has authored 16 papers receiving a total of 782 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 9 papers in Genetics and 3 papers in Sensory Systems. Recurrent topics in Killian S. Hanlon's work include Virus-based gene therapy research (9 papers), CRISPR and Genetic Engineering (7 papers) and RNA Interference and Gene Delivery (6 papers). Killian S. Hanlon is often cited by papers focused on Virus-based gene therapy research (9 papers), CRISPR and Genetic Engineering (7 papers) and RNA Interference and Gene Delivery (6 papers). Killian S. Hanlon collaborates with scholars based in United States, Ireland and Netherlands. Killian S. Hanlon's co-authors include Casey A. Maguire, David P. Corey, Adrienn Volak, Bence György, Benjamin P. Kleinstiver, Maryna V. Ivanchenko, Cole W. Peters, Camilla Lööv, Niclas E. Bengtsson and Mikołaj Piotr Zaborowski and has published in prestigious journals such as Nature Communications, Scientific Reports and Trends in Pharmacological Sciences.

In The Last Decade

Killian S. Hanlon

16 papers receiving 768 citations

Hit Papers

High levels of AAV vector integration into CRISPR-induced... 2019 2026 2021 2023 2019 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Killian S. Hanlon United States 12 633 325 163 63 55 16 782
Adrienn Volak United States 9 759 1.2× 337 1.0× 167 1.0× 51 0.8× 53 1.0× 9 954
Wei-Hsi Yeh United States 10 1.7k 2.6× 566 1.7× 208 1.3× 73 1.2× 61 1.1× 11 1.8k
Frank M. Dyka United States 18 1.1k 1.7× 425 1.3× 213 1.3× 228 3.6× 55 1.0× 32 1.2k
Heikki Turunen United States 11 559 0.9× 385 1.2× 46 0.3× 78 1.2× 20 0.4× 16 798
Sonia M. Rocha-Sanchez United States 15 390 0.6× 79 0.2× 325 2.0× 62 1.0× 67 1.2× 23 751
Kwanghyuk Lee United States 16 566 0.9× 183 0.6× 310 1.9× 25 0.4× 80 1.5× 39 1.0k
Xinde Hu China 12 877 1.4× 270 0.8× 51 0.3× 23 0.4× 18 0.3× 14 967
Sarah Wassmer United States 7 411 0.6× 178 0.5× 174 1.1× 46 0.7× 60 1.1× 18 565
Déborah Scheffer United States 13 532 0.8× 130 0.4× 548 3.4× 48 0.8× 149 2.7× 14 960

Countries citing papers authored by Killian S. Hanlon

Since Specialization
Citations

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

Fields of papers citing papers by Killian S. Hanlon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Killian S. Hanlon

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

All Works

16 of 16 papers shown
1.
Hanlon, Killian S., Ming Cheng, Jae Ryun Ryu, et al.. (2024). In vivo selection in non-human primates identifies AAV capsids for on-target CSF delivery to spinal cord. Molecular Therapy. 32(8). 2584–2603. 6 indexed citations
2.
Ramirez, Servio H., Jonathan F. Hale, Siobhán McCarthy, et al.. (2023). An Engineered Adeno-Associated Virus Capsid Mediates Efficient Transduction of Pericytes and Smooth Muscle Cells of the Brain Vasculature. Human Gene Therapy. 34(15-16). 682–696. 11 indexed citations
3.
Chadderton, Naomi, Arpad Palfi, Daniel Maloney, et al.. (2023). Optimisation of AAV-NDI1 Significantly Enhances Its Therapeutic Value for Correcting Retinal Mitochondrial Dysfunction. Pharmaceutics. 15(2). 322–322. 5 indexed citations
4.
Peters, Cole W., Killian S. Hanlon, Maryna V. Ivanchenko, et al.. (2023). Rescue of hearing by adenine base editing in a humanized mouse model of Usher syndrome type 1F. Molecular Therapy. 31(8). 2439–2453. 21 indexed citations
5.
Beharry, Adam W., Yi Gong, James C. Kim, et al.. (2021). The AAV9 Variant Capsid AAV-F Mediates Widespread Transgene Expression in Nonhuman Primate Spinal Cord After Intrathecal Administration. Human Gene Therapy. 33(1-2). 61–75. 17 indexed citations
6.
Peters, Cole W., Casey A. Maguire, & Killian S. Hanlon. (2021). Delivering AAV to the Central Nervous and Sensory Systems. Trends in Pharmacological Sciences. 42(6). 461–474. 31 indexed citations
7.
Ivanchenko, Maryna V., Killian S. Hanlon, Cole W. Peters, et al.. (2021). AAV-S: A versatile capsid variant for transduction of mouse and primate inner ear. Molecular Therapy — Methods & Clinical Development. 21. 382–398. 47 indexed citations
8.
Hanlon, Killian S., Adrienn Volak, Amine Meliani, et al.. (2020). In vivo engineering of lymphocytes after systemic exosome-associated AAV delivery. Scientific Reports. 10(1). 4544–4544. 25 indexed citations
9.
Solinge, Thomas S. van, Erik R. Abels, Killian S. Hanlon, et al.. (2020). Versatile Role of Rab27a in Glioma: Effects on Release of Extracellular Vesicles, Cell Viability, and Tumor Progression. Frontiers in Molecular Biosciences. 7. 554649–554649. 10 indexed citations
10.
Ivanchenko, Maryna V., Killian S. Hanlon, J. Lafond, et al.. (2020). Preclinical testing of AAV9-PHP.B for transgene expression in the non-human primate cochlea. Hearing Research. 394. 107930–107930. 45 indexed citations
11.
Millington‐Ward, Sophia, Naomi Chadderton, Killian S. Hanlon, et al.. (2020). Novel 199 base pair NEFH promoter drives expression in retinal ganglion cells. Scientific Reports. 10(1). 16515–16515. 9 indexed citations
12.
Hanlon, Killian S., Tetyana P. Buzhdygan, Ming J. Cheng, et al.. (2019). Selection of an Efficient AAV Vector for Robust CNS Transgene Expression. Molecular Therapy — Methods & Clinical Development. 15. 320–332. 103 indexed citations
13.
Hanlon, Killian S., Benjamin P. Kleinstiver, Sara P. Garcia, et al.. (2019). High levels of AAV vector integration into CRISPR-induced DNA breaks. Nature Communications. 10(1). 4439–4439. 289 indexed citations breakdown →
14.
György, Bence, Maryna V. Ivanchenko, Killian S. Hanlon, et al.. (2018). Gene Transfer with AAV9-PHP.B Rescues Hearing in a Mouse Model of Usher Syndrome 3A and Transduces Hair Cells in a Non-human Primate. Molecular Therapy — Methods & Clinical Development. 13. 1–13. 125 indexed citations
15.
Hanlon, Killian S., Naomi Chadderton, Arpad Palfi, et al.. (2017). A Novel Retinal Ganglion Cell Promoter for Utility in AAV Vectors. Frontiers in Neuroscience. 11. 521–521. 24 indexed citations
16.
Rogers, Sherry L., Sally L. Palm, Paul C. Letourneau, et al.. (1988). Cell adhesion and neurite extension in response to two proteolytic fragments of laminin. Journal of Neuroscience Research. 21(2-4). 315–322. 14 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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