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Jo Vandesompele

Researcher at Ghent University

Publications -  406
Citations -  67052

Jo Vandesompele is an academic researcher from Ghent University. The author has contributed to research in topics: Neuroblastoma & microRNA. The author has an hindex of 88, co-authored 383 publications receiving 59368 citations. Previous affiliations of Jo Vandesompele include Washington University in St. Louis & Ghent University Hospital.

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Quantitative Real Time Polymerase Chain Reaction for measurement of human Interleukin – 5 receptor alpha spliced isoforms mRNA

TL;DR: An accurate and reliable assay for quantification of interleukin-5 receptor alpha mRNA isoforms over a broad dynamic range of input molecules is developed to allow a better understanding of the regulatory mechanisms of the hIL-5Rα gene and hence its role in the pathogenesis of chronic inflammatory diseases.
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Stage 4S neuroblastoma tumors show a characteristic DNA methylation portrait

TL;DR: In this article, the DNA methylome of stage 4S neuroblastoma (NB) was analyzed using methyl-CpG-binding domain (MBD) sequencing data.
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Differential polyadenylation of ribosomal RNA during post-transcriptional processing in Leishmania

TL;DR: Another unusual phenomenon is reported as it is demonstrated that precursor ribosomal RNA can be extensively polyadenylated during post-transcriptional processing[dagger], and the degree of precursor rRNApolyadenylation is variable in different strains and in the different life-stages of a strain.
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High resolution tiling-path BAC array deletion mapping suggests commonly involved 3p21-p22 tumor suppressor genes in neuroblastoma and more frequent tumors.

TL;DR: The present data significantly extend previous findings and now firmly establish critical regions on 3p implicated in neuroblastoma, Interestingly, the 2 proximal regions coincide with previously defined SROs on 3 p21.3 in more frequent tumors including lung and breast cancer.
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decodeRNA- predicting non-coding RNA functions using guilt-by-association.

TL;DR: DecodeRNA as mentioned in this paper provides functional contexts for both human lncRNAs and microRNAs in 29 cancer and 12 normal tissue types with state-of-the-art data mining and visualization options, easy access to results and a straightforward user interface.