Rainer Pudimat

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RNA binding proteins recognize RNA targets in a sequence specific manner. Apart from the sequence, the secondary structure context of the binding site also affects the binding affinity. Binding sites are often located in single-stranded RNA regions and it was shown that the sequestration of a binding motif in a double-strand abolishes protein binding. Thus,(More)
MOTIVATION The identification of transcription factor binding sites in promoter sequences is an important problem, since it reveals information about the transcriptional regulation of genes. For analysing transcriptional regulation, computational approaches for predicting putative binding sites are applied. Commonly used stochastic models for binding sites(More)
The YTH (YT521-B homology) domain was identified by sequence comparison and is found in 174 different proteins expressed in eukaryotes. It is characterized by 14 invariant residues within an alpha-helix/beta-sheet structure. Here we show that the YTH domain is a novel RNA binding domain that binds to a short, degenerated, single-stranded RNA sequence motif.(More)
BioBayesNet is a new web application that allows the easy modeling and classification of biological data using Bayesian networks. To learn Bayesian networks the user can either upload a set of annotated FASTA sequences or a set of pre-computed feature vectors. In case of FASTA sequences, the server is able to generate a wide range of sequence and structural(More)
The prediction of transcription factor binding sites is an important problem, since it reveals information about the transcriptional regulation of genes. A commonly used representation of these sites are position specific weight matrices which show weak predictive power. We introduce a feature-based modelling approach, which is able to deal with various(More)
Alternative splicing is a major contributor to the diversity of eukaryotic transcriptomes and proteomes. Currently, large scale detection of alternative splicing using expressed sequence tags (ESTs) or microarrays does not capture all alternative splicing events. Moreover, for many species genomic data is being produced at a far greater rate than(More)
Motivation: Biological research produces a wealth of measured data. Neither it is easy for biologists to postulate hypotheses about the behaviour or structure of the observed entity because the relevant properties measured are not seen in the ocean of measurements. Nor it is easy to design machine learning algorithms to classify or cluster the data items(More)
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