Gareth J. Sullivan

4.3k total citations
68 papers, 2.9k citations indexed

About

Gareth J. Sullivan is a scholar working on Molecular Biology, Genetics and Biomedical Engineering. According to data from OpenAlex, Gareth J. Sullivan has authored 68 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Molecular Biology, 12 papers in Genetics and 10 papers in Biomedical Engineering. Recurrent topics in Gareth J. Sullivan's work include Pluripotent Stem Cells Research (24 papers), CRISPR and Genetic Engineering (12 papers) and Mitochondrial Function and Pathology (11 papers). Gareth J. Sullivan is often cited by papers focused on Pluripotent Stem Cells Research (24 papers), CRISPR and Genetic Engineering (12 papers) and Mitochondrial Function and Pathology (11 papers). Gareth J. Sullivan collaborates with scholars based in Norway, United Kingdom and United States. Gareth J. Sullivan's co-authors include Richard Siller, In‐Hyun Park, Brian McStay, Judy Fletcher, Ian Wilmut, Sebastian Greenhough, Elena Naumovska, Anna Kostareva, Jarle Vaage and Maria Bogdanova and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.

In The Last Decade

Gareth J. Sullivan

68 papers receiving 2.8k citations

Peers

Gareth J. Sullivan

SURGE

GENET

HEPAT

Satoshi Okamoto Japan

Elizabeth L. Buza United States

Yi Arial Zeng China

John Lincecum United States

Kiavash Movahedi Belgium

Yujiro Tanaka Japan

Mercedes Costell Spain

Claudia Korn Germany

Przemysław Błyszczuk Switzerland

Lucia Manzoli Italy

Satoshi Okamoto Japan

Gareth J. Sullivan

2.8k ×1.5

438 ×1.0

SURGE

420 ×1.1

168 ×0.5

GENET

260 ×0.9

HEPAT

Citations per year, relative to Gareth J. Sullivan Gareth J. Sullivan (= 1×) peers Satoshi Okamoto

Countries citing papers authored by Gareth J. Sullivan

Since Specialization

Citations

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

Fields of papers citing papers by Gareth J. Sullivan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gareth J. Sullivan. 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 Gareth J. Sullivan. The network helps show where Gareth J. Sullivan may publish in the future.

Co-authorship network of co-authors of Gareth J. Sullivan

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

All Works

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20 of 20 papers shown

Harrison, Sean, et al.. (2024). Effect of hypoxia on aquaporins and hepatobiliary transport systems in human hepatic cells. Pediatric Research. 97(1). 195–201. 1 indexed citations

Liang, Kristina Xiao, Jessica Furriol, Mathias Ziegler, et al.. (2024). Activation of Neurotoxic Astrocytes Due to Mitochondrial Dysfunction Triggered by POLG Mutation. International Journal of Biological Sciences. 20(8). 2860–2880. 6 indexed citations

Harrison, Sean, et al.. (2024). Parenteral nutrition emulsion inhibits CYP3A4 in an iPSC derived liver organoids testing platform. Journal of Pediatric Gastroenterology and Nutrition. 78(5). 1047–1058. 2 indexed citations

Stavik, Benedicte, et al.. (2023). “iPSC-derived liver organoids and inherited bleeding disorders: Potential and future perspectives”. Frontiers in Physiology. 14. 1094249–1094249. 3 indexed citations

Taebnia, Nayere, Sean Harrison, Sonia Youhanna, et al.. (2023). 3D microperfusion of mesoscale human microphysiological liver models improves functionality and recapitulates hepatic zonation. Acta Biomaterialia. 171. 336–349. 17 indexed citations

Furriol, Jessica, et al.. (2023). Deoxyribonucleoside treatment rescues EtBr ‐induced mtDNA depletion in iPSC ‐derived neural stem cells with POLG mutations. The FASEB Journal. 37(9). e23139–e23139. 2 indexed citations

Wang, Wei, Sarah L. Fordyce Martin, Diana L. Bordin, et al.. (2021). Increased p53 signaling impairs neural differentiation in HUWE1-promoted intellectual disabilities. Cell Reports Medicine. 2(4). 100240–100240. 5 indexed citations

Nido, Gonzalo S., et al.. (2021). Distinct Mitochondrial Remodeling During Mesoderm Differentiation in a Human-Based Stem Cell Model. Frontiers in Cell and Developmental Biology. 9. 8 indexed citations

Harrison, Sean, et al.. (2021). 3D Printed Tooling for Injection Molded Microfluidics. Macromolecular Materials and Engineering. 306(11). 14 indexed citations

10.

Kim, Jonghun, Gareth J. Sullivan, & In‐Hyun Park. (2021). How well do brain organoids capture your brain?. iScience. 24(2). 102063–102063. 40 indexed citations

11.

Liang, Kristina Xiao, Charalampos Tzoulis, Mathias Ziegler, et al.. (2020). Disease‐specific phenotypes in iPSC ‐derived neural stem cells with POLG mutations. EMBO Molecular Medicine. 12(10). e12146–e12146. 37 indexed citations

12.

Xiang, Yangfei, Yoshiaki Tanaka, Benjamin Patterson, et al.. (2020). Dysregulation of BRD4 Function Underlies the Functional Abnormalities of MeCP2 Mutant Neurons. Molecular Cell. 79(1). 84–98.e9. 63 indexed citations

13.

Siller, Richard, et al.. (2016). Development of a rapid screen for the endodermal differentiation potential of human pluripotent stem cell lines. Scientific Reports. 6(1). 37178–37178. 31 indexed citations

14.

Siller, Richard, Sebastian Greenhough, Elena Naumovska, & Gareth J. Sullivan. (2015). Small-Molecule-Driven Hepatocyte Differentiation of Human Pluripotent Stem Cells. Stem Cell Reports. 4(5). 939–952. 154 indexed citations

15.

Dajani, Rana, et al.. (2013). Investigation of Rett syndrome using pluripotent stem cells. Journal of Cellular Biochemistry. 114(11). 2446–2453. 18 indexed citations

16.

Bilican, Bilada, Andrea Serio, Sami J. Barmada, et al.. (2012). Mutant induced pluripotent stem cell lines recapitulate aspects of TDP-43 proteinopathies and reveal cell-specific vulnerability. Proceedings of the National Academy of Sciences. 109(15). 5803–5808. 257 indexed citations

17.

Yamazaki, Tomohiro, Shi Chen, Yong Yu, et al.. (2012). FUS-SMN Protein Interactions Link the Motor Neuron Diseases ALS and SMA. Cell Reports. 2(4). 799–806. 204 indexed citations

18.

Kim, Kun‐Yong, Yong Wook Jung, Gareth J. Sullivan, Leeyup Chung, & In‐Hyun Park. (2012). Cellular reprogramming: a novel tool for investigating autism spectrum disorders. Trends in Molecular Medicine. 18(8). 463–471. 14 indexed citations

19.

Ruzov, Alexey, Andrea Serio, Tatiana Dudnakova, et al.. (2011). Lineage-specific distribution of high levels of genomic. Cell Research. 21(9). 1332–1342. 157 indexed citations

20.

Woodward, Martin J. & Gareth J. Sullivan. (1991). Nucleotide sequence of a repetitive element isolated from Leptospira interrogans serovar hardjo type hardjo-bovis. Journal of General Microbiology. 137(5). 1101–1109. 15 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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