Takustr. 9, Room 005

Wednesday, 12 am-14 pm

Non-coding RNAs have been recognized as an abundant class of genes with a wide spectrum of functions, often performed through their structure. Given their involvement in almost every biological process, in the last 10 years increasing attention has been given to RNA bioinformatics, the discipline devoted to the development of computational tools and methodologies for the analysis of RNA sequence, structure and function.
This seminar is meant for master students and the goal is to look deeper at some selected papers describing algorithms or statistical methods for ncRNA promoter and gene finding, RNA structure prediction, ncRNA functional analysis, RNA motif discovery and RNA-protein interaction prediction. In addition, the aim will be to use the articles as a starting point to critically assess the methodologies, and understand how they can be improved or extended to other contexts. The proposed journal articles are listed below and this list can be extended or changed depending on the number of participants. The number of participants will be limited to 14.


Non-coding RNA Gene finding methods


1) A statistical model for prediction and scoring of novel microRNA genes from deep sequencing data

presentation_miRDeep ...by Valentin

2) Prediction of non-coding RNA genes using comparative genomics (RNAz)

presentation_RNAz ..by Marcel

3) Computational discovery of transcripts with conserved splice sites

presentation_phylogenSVM ..by Adrian

Analysis of RNA sequence and structure


4) RNA consensus secondary structure prediction from multiple sequence alignments (RNAalifold)

presentation_RNAalifold ..by Moritz

5) Analysis of RNA secondary structure in vivo - PARS

presentation_PARSscores ..by Fritz

6) Analysis of Secondary Structure in vivo - DMS


presentation_DMSscores ..by Arsene

7) An overview on the analysis of RNA-seq data

presentation_RNAseq ..by Matthias


Discovery of RNA motifs


8) De Novo discovery of functional motifs in mRNAs using context-free grammars

presentation_TEISER ..by Timo

9) Prediction of RNA motifs using a covariance model

presentation_CMfinder ..by Annkatrin


RNA-binding site predictions


10) Probabilistic model for the prediction of protein binding sites for RNA sequences and structures

presentation_RNAcontext ..by Ria

11) A method to identify differential RNA binding proteins from iCLIP data using a Hidden Markov Model

presentation_dCLIP ..by Jakob

12) Overview on the analysis of CLIP-seq data (mainly iCLIP)

presentation_iCLIP ..by Sabrina


Functional analysis of non-coding RNA targets


13) A machine learning method (regression model)  to rank microRNA target genes

presentation_miRSVR ..by Stefan

14) Combinatorial miRNA target prediction

presentation_picTar ..by Herbert

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