Auflistung nach Autor:in "Stadler, Peter F."
1 - 9 von 9
Treffer pro Seite
Sortieroptionen
- JournalBig Data Competence Center ScaDS Dresden/Leipzig: Overview and selected research activities(Datenbank-Spektrum: Vol. 19, No. 1, 2019) Rahm, Erhard; Nagel, Wolfgang E.; Peukert, Eric; Jäkel, René; Gärtner, Fabian; Stadler, Peter F.; Wiegreffe, Daniel; Zeckzer, Dirk; Lehner, Wolfgang
- KonferenzbeitragComparative analysis of cyclic sequences: Viroids and other small circular RNAs(German Conference on Bioinformatics, 2006) Mosig, Axel; Hofacker, Ivo L.; Stadler, Peter F.The analysis of small circular sequences requires specialized tools. While the differences between linear and circular sequences can be neglected in the case of long molecules such as bacterial genomes since in practice all analysis is performed in sequence windows, this is not true for viroids and related sequences which are usually only a few hundred basepairs long. In this contribution we present basic algorithms and corresponding software for circular RNAs. In particular, we discuss the problem of pairwise and multiple cyclic sequence alignments with affine gap costs, and an extension of a recent approach to circular RNA folding to the computation of consensus structures.
- KonferenzbeitragConserved RNA pseudoknots(German Conference on Bioinformatics 2004, GCB 2004, 2004) Thurner, Caroline; Hofacker, Ivo L.; Stadler, Peter F.Pseudoknots are essential for the functioning of many small RNA molecules. In addition, viral RNAs often exhibit pseudoknots that are required at various stages of the viral life-cycle. Techniques for detecting evolutionarily conserved, and hence most likely functional RNA pseudoknots, are therefore of interest. Here we present an extension of the alidot approach that extracts conserved secondary structures from a multiple sequence alignment and predicted secondary structures of the individual sequences. In contrast to purely phylogenetic methods, this approach yields good results already for small samples of 10 sequences or even less.
- KonferenzbeitragMaximum likelihood estimation of weight matrices for targeted homology search(German conference on bioinformatics 2009, 2009) Menzel, Peter; Gorodkin, Jan; Stadler, Peter F.Genome annotation relies to a large extent on the recognition of homologs to already known genes. The starting point for such protocols is a collection of known sequences from one or more species, from which a model is constructed – either automatically or manually – that encodes the defining features of a single gene or a gene family. The quality of these models eventually determines the success rate of the homology search. We propose here a novel approach to model construction that not only captures the characteristic motifs of a gene, but are also adjusts the search pattern by including phylogenetic information. Computational tests demonstrate that this can lead to a substantial improvement of homology search models.
- KonferenzbeitragMemory efficient folding algorithms for circular RNA secondary structures(German Conference on Bioinformatics 2005 (GCB 2005), 2005) Hofacker, Ivo L.; Stadler, Peter F.A small class of RNA molecules, in particular the tiny genomes of viroids, are circular. Yet most structure prediction algorithms handle only linear RNAs. The most straightforward approach is to compute circular structures from "internal" and "external" substructures separated by a base pair. This is incompatible, however, with the memory-saving approach of the Vienna RNA Package which builds a linear RNA structure from shorter (internal) structures only. Here we describe how circular secondary structures can be obtained without additional memory requirements as a kind of "post-processing" of the linear structures.
- KonferenzbeitragMultiple sequence alignment with user-defined constraints(German Conference on Bioinformatics 2004, GCB 2004, 2004) Morgenstern, Burkhard; Prohaska, Sonja J.; Werner, Nadine; Weyer-Menkhoff, Jan; Schneider, Isabelle; Subramanian, Amarendran R.; Stadler, Peter F.In many situations, automated multi-alignment programs are not able to correctly align families of nucleic acid or protein sequences. Distantly related sequences are generally hard to align, and sequence duplications may present additional challenges to standard alignment algorithms. In the present paper, we describe a semiautomatic approach to multiple sequence alignment. The user can specify parts of the sequences that are thought to be related to each other; our software program will use these sites as anchor points and create a multiple alignment respecting these userdefined constraints. By using functionally, structurally or evolutionarily related positions of the input sequences as anchor points, the proposed method can produce alignments that are biologically more meaningful than alignments produced by fully automated procedures. We apply our approach to genomic sequences around the Hox gene cluster. As a by-product, we obtain useful insights for the further development of alignment algorithms. The described alignment approach has been integrated into the tracker software system.
- KonferenzbeitragQuantitative comparison of genomic-wide protein domain distributions(German Conference on Bioinformatics 2010, 2010) Parikesit, Arli A.; Stadler, Peter F.; Prohaska, Sonja J.Investigations into the origins and evolution of regulatory mechanisms require quantitative estimates of the abundance and co-occurrence of functional protein domains among distantly related genomes. Currently available databases, such as the SUPERFAMILY, are not designed for quantitative comparisons since they are built upon transcript and protein annotations provided by the various different genome annotation projects. Large biases are introduced by the differences in genome annotation protocols, which strongly depend on the availability of transcript information and well-annotated closely related organisms. Here we show that the combination of de novo gene predictors and subsequent HMM-based annotation of SCOP domains in the predicted peptides leads to consistent estimates with acceptable accuracy that in particular can be utilized for systematic studies of the evolution of protein domain occurrences and co-occurrences. As an application, we considered four major classes of DNA binding domains: zink-finger, leucine-zipper, winged-helix, and HMG-box. We found that different types of DNA binding domains systematically avoid each other throughout the evolution of Eukarya. In contrast, DNA binding domains belonging to the same superfamily readily co-occur in the same protein.
- KonferenzbeitragTanimoto’s Best Barbecue: Discovering Regulatory Modules using Tanimoto Scores(German conference on bioinformatics – GCB 2007, 2007) Menzel, Peter; Stadler, Peter F.; Mosig, AxelWe present a combinatorial method for discovering cis-regulatory modules in promoter sequences. Our approach combines “sliding window” approaches with a scoring function based on the so-called Tanimoto score. This allows to identify sets of binding sites that tend to occur preferentially in the vicinity of each other in a given set of promoter sequences belonging to co-expressed or orthologous genes. We bench- mark our method on a data set derived from muscle-specific genes, demonstrating that our approach is capable of identifying modules that were identified as functional in previous studies.
- KonferenzbeitragThermodynamics of RNA-RNA binding(German Conference on Bioinformatics 2005 (GCB 2005), 2005) Mückstein, Ulrike; Tafer, Hakim; Hackermüller, Jörg; Bernhart, Stephan H.; Stadler, Peter F.; Hofacker, Ivo L.We present an extension of the standard partition function approach to RNA secondary structures that computes the probabilities Pu[i, j] that a sequence interval [i, j] is unpaired. Comparison with experimental data shows that Pu[i, j] can be applied as a significant determinant of local target site accessibility for RNA interference (RNAi). Furthermore, these quantities can be used to rigorously determine binding free energies of short oligomers to large mRNA targets. The resource consumption is comparable to a single partition function computation for the large target molecule. We can show that RNAi efficiency correlates well with the binding probabilities of siRNAs to their respective mRNA target.