Niall Barron

3.5k total citations
105 papers, 2.7k citations indexed

About

Niall Barron is a scholar working on Molecular Biology, Biomedical Engineering and Genetics. According to data from OpenAlex, Niall Barron has authored 105 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 92 papers in Molecular Biology, 19 papers in Biomedical Engineering and 13 papers in Genetics. Recurrent topics in Niall Barron's work include Viral Infectious Diseases and Gene Expression in Insects (47 papers), RNA Interference and Gene Delivery (21 papers) and CRISPR and Genetic Engineering (19 papers). Niall Barron is often cited by papers focused on Viral Infectious Diseases and Gene Expression in Insects (47 papers), RNA Interference and Gene Delivery (21 papers) and CRISPR and Genetic Engineering (19 papers). Niall Barron collaborates with scholars based in Ireland, United Kingdom and United States. Niall Barron's co-authors include Martin Clynes, Paula Meleady, Padraig Doolan, Colin Clarke, A. P. McHale, Patrick Gammell, Michael Henry, Nga T. Lao, L. McHale and Paul Kelly and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and PLoS ONE.

In The Last Decade

Niall Barron

103 papers receiving 2.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Niall Barron Ireland 30 2.1k 421 413 353 317 105 2.7k
Liqin Wang China 27 1.7k 0.8× 445 1.1× 280 0.7× 205 0.6× 473 1.5× 90 3.0k
Michael J. Powell United States 28 1.4k 0.7× 146 0.3× 448 1.1× 417 1.2× 187 0.6× 76 3.0k
Chenguang Fan United States 31 2.1k 1.0× 197 0.5× 391 0.9× 117 0.3× 181 0.6× 58 2.9k
Peng Sun China 28 1.3k 0.6× 683 1.6× 146 0.4× 392 1.1× 350 1.1× 114 2.5k
Zheng Cui China 24 1.7k 0.8× 352 0.8× 167 0.4× 234 0.7× 172 0.5× 67 2.8k
Byoung Chul Park South Korea 30 1.6k 0.7× 215 0.5× 158 0.4× 106 0.3× 287 0.9× 107 2.3k
Lihua Lai China 28 1.8k 0.8× 946 2.2× 209 0.5× 169 0.5× 374 1.2× 58 3.1k
Ansar Karimian Iran 23 1.5k 0.7× 563 1.3× 119 0.3× 169 0.5× 466 1.5× 38 2.4k
Tongcun Zhang China 29 1.4k 0.7× 626 1.5× 158 0.4× 183 0.5× 441 1.4× 118 2.4k
Khaled Seidi Iran 26 1.2k 0.6× 524 1.2× 97 0.2× 696 2.0× 734 2.3× 37 2.8k

Countries citing papers authored by Niall Barron

Since Specialization
Citations

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

Fields of papers citing papers by Niall Barron

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Niall Barron

This figure shows the co-authorship network connecting the top 25 collaborators of Niall Barron. A scholar is included among the top collaborators of Niall Barron 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 Niall Barron. Niall Barron 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.
2.
Tzani, Ioanna, Paul Kelly, Lin Zhang, et al.. (2024). Detection of host cell microprotein impurities in antibody drug products. Nature Communications. 15(1). 8605–8605. 3 indexed citations
3.
Lao, Nga T. & Niall Barron. (2023). Enhancing recombinant protein and viral vector production in mammalian cells by targeting the YTHDF readers of N6‐methyladenosine in mRNA. Biotechnology Journal. 18(4). e2200451–e2200451. 7 indexed citations
4.
Tzani, Ioanna, Nicholas P. Herrmann, Sara Carillo, et al.. (2021). Tracing production instability in a clonally derived CHO cell line using single‐cell transcriptomics. Biotechnology and Bioengineering. 118(5). 2016–2030. 18 indexed citations
5.
Henry, Michael, Niall Barron, Clair Gallagher, et al.. (2021). Differential expression of miRNAs and functional role of mir-200a in high and low productivity CHO cells expressing an Fc fusion protein. Biotechnology Letters. 43(8). 1551–1563. 6 indexed citations
6.
Tzani, Ioanna, et al.. (2020). Expanding the Chinese hamster ovary cell long noncoding RNA transcriptome using RNASeq. Biotechnology and Bioengineering. 117(10). 3224–3231. 12 indexed citations
7.
Tzani, Ioanna, Clair Gallagher, Paul Kelly, et al.. (2020). Subphysiological temperature induces pervasive alternative splicing in Chinese hamster ovary cells. Biotechnology and Bioengineering. 117(8). 2489–2503. 8 indexed citations
8.
Kaushik, Prashant, et al.. (2020). LC-MS/MS-based quantitative proteomic and phosphoproteomic analysis of CHO-K1 cells adapted to growth in glutamine-free media. Biotechnology Letters. 42(12). 2523–2536. 10 indexed citations
9.
10.
Lao, Nga T., et al.. (2019). An arginase-based system for selection of transfected CHO cells without the use of toxic chemicals. Journal of Biological Chemistry. 294(49). 18756–18768. 14 indexed citations
11.
12.
Kelly, Paul, et al.. (2018). From media to mitochondria–rewiring cellular energy metabolism of Chinese hamster ovary cells for the enhanced production of biopharmaceuticals. Current Opinion in Chemical Engineering. 22. 71–80. 8 indexed citations
13.
Henry, Michael, Clair Gallagher, Ronan M. Kelly, et al.. (2018). Clonal variation in productivity and proteolytic clipping of an Fc-fusion protein in CHO cells: Proteomic analysis suggests a role for defective protein folding and the UPR. Journal of Biotechnology. 281. 21–30. 11 indexed citations
14.
Jadhav, Vaibhav, Matthias Hackl, Aliaksandr Druz, et al.. (2013). CHO microRNA engineering is growing up: Recent successes and future challenges. Biotechnology Advances. 31(8). 1501–1513. 67 indexed citations
15.
Kelly, Paul, Clair Gallagher, Nga T. Lao, et al.. (2013). CHO cell culture longevity and recombinant protein yield are enhanced by depletion of miR‐7 activity via sponge decoy vectors. Biotechnology Journal. 9(3). 396–404. 45 indexed citations
16.
Devereux, Michael, Niall Barron, Malachy McCann, et al.. (2012). Potent oxidative DNA cleavage by the di-copper cytotoxin: [Cu2(μ-terephthalate)(1,10-phen)4]2+. Chemical Communications. 48(55). 6906–6906. 53 indexed citations
17.
Barron, Niall, Joanne Keenan, Patrick Gammell, et al.. (2011). Biochemical relapse following radical prostatectomy and miR‐200a levels in prostate cancer. The Prostate. 72(11). 1193–1199. 44 indexed citations
18.
Melville, Mark, Padraig Doolan, William Mounts, et al.. (2011). Development and characterization of a Chinese hamster ovary cell-specific oligonucleotide microarray. Biotechnology Letters. 33(9). 1773–1779. 16 indexed citations
19.
Egan, Brendan, Brian P. Carson, Pablo M. García-Rovés, et al.. (2010). Exercise intensity-dependent regulation of peroxisome proliferator-activated receptor γ coactivator-1α mRNA abundance is associated with differential activation of upstream signalling kinases in human skeletal muscle. The Journal of Physiology. 588(10). 1779–1790. 305 indexed citations
20.
Nimkarn, Saroj, David D. Brandon, S. Cunningham‐Rundles, et al.. (2001). Resistance to multiple steroids in two sisters. The Journal of Steroid Biochemistry and Molecular Biology. 76(1-5). 161–166. 8 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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