C
Cathal Seoighe
Researcher at National University of Ireland, Galway
Publications - 114
Citations - 8223
Cathal Seoighe is an academic researcher from National University of Ireland, Galway. The author has contributed to research in topics: Gene & Genome. The author has an hindex of 37, co-authored 108 publications receiving 7381 citations. Previous affiliations of Cathal Seoighe include University College Dublin & South African National Bioinformatics Institute.
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Journal ArticleDOI
Allele-specific splicing effects on DKKL1 and ZNF419 transcripts in HeLa cells.
Grace Martin,S. Duygu Selcuklu,Katherine Schouest,Victoria Nembaware,Peter C. McKeown,Cathal Seoighe,Charles Spillane +6 more
TL;DR: The impact of SNP mutations on mRNA splicing, and its biological relevance, can be predicted by integrating SNP position with available data on relative isoform abundance in human cell lines.
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Integrative analysis of mRNA expression and half-life data reveals trans-acting genetic variants associated with increased expression of stable transcripts.
TL;DR: It is proposed that a cis-eQTL of SNRPB may be directly responsible for inter-individual variation in relative expression of long-lived versus short-lived transcript in Asian populations and, in support of this hypothesis, knockdown ofSNRPB results in a significant reduction in the relative expression.
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Selective Toxicity of BIP Inducer X Towards Microglia and Oligodendrocytes In In Vitro and Ex Vivo Models of Myelination
Una FitzGerald,Enrico Bagnoli,Eugenia Pugliese,Bandla Sravanthi,Siobhán Cleary,Lorna Hayden,Diana Arseni,Jill McMahon,Cathal Seoighe,Christopher Linington,Heinz-Peter Nasheuer +10 more
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vcfView: An Extensible Data Visualization and Quality Assurance Platform for Integrated Somatic Variant Analysis.
Brian O’Sullivan,Cathal Seoighe +1 more
TL;DR: In this paper, the authors used targeted methods to assay specific cancer driver mutations, and found that high-level mutations can have critical prognostic and therapeutic implications for cancer patients, although targeted methods are often used to test specific cancer drivers.
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Somatic mutations inferred from RNA-seq data highlight the Contribution of replication timing to mutation rate variation in a model plant.
TL;DR: In this article, the authors adapted a recently developed method for inferring somatic mutations from bulk RNA-seq data and applied it to a large collection of Arabidopsis thaliana accessions.