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Maria Katsantoni

Researcher at University of Basel

Publications -  7
Citations -  212

Maria Katsantoni is an academic researcher from University of Basel. The author has contributed to research in topics: Compendium & ENCODE. The author has an hindex of 3, co-authored 4 publications receiving 68 citations. Previous affiliations of Maria Katsantoni include Swiss Institute of Bioinformatics.

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CLIP and complementary methods

TL;DR: The prospect of integrating data obtained by CLIP with complementary methods to gain a comprehensive view of RNP assembly and remodelling, unravel the spatial and temporal dynamics of RNPs in specific cell types and subcellular compartments and understand how defects in RNPs can lead to disease are discussed.
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The SIB Swiss Institute of bioinformatics' resources: Focus on curated databases

Lisandra Aguilar Bultet, +676 more
TL;DR: An overview of S IB's resources and competence areas is provided, with a strong focus on curated databases and SIB's most popular and widely used resources.
Journal ArticleDOI

Improved analysis of (e)CLIP data with RCRUNCH yields a compendium of RNA-binding protein binding sites and motifs

TL;DR: RCRUNCH as discussed by the authors is an end-to-end solution to CLIP data analysis for identification of binding sites and sequence specificity of RNA-binding proteins, which can analyze not only reads that map uniquely to the genome but also those that map to multiple genome locations or across splice boundaries and can consider various types of background in the estimation of read enrichment.
Posted ContentDOI

Improved analysis of (e)CLIP data with RCRUNCH yields a compendium of RNA-binding protein binding sites and motifs

TL;DR: RCRUNCH as mentioned in this paper is an end-to-end solution to CLIP data analysis for identification of binding sites and sequence specificity of RNA-binding proteins, which can analyze not only reads that map uniquely to the genome, but also those that map to multiple genome locations or across splice boundaries, and can consider various types of background in the estimation of read enrichment.