J. Stoye

Publications of J. Stoye

• QAlign: quality-based multiple alignments with dynamic phylogenetic analysis.

  Authors: M. Sammeth, J Rothgänger, W Esser, J Albert, J. Stoye, D Harmsen

  Bioinformatics (Oxford, England). 09/2003; 19(12):1592-3.

  Integrating different alignment strategies, a layout editor and tools deriving phylogenetic trees in a 'multiple alignment environment' helps to investigate and enhance results of multiple sequenceIntegrating different alignment strategies, a layout editor and tools deriving phylogenetic trees in a 'multiple alignment environment' helps to investigate and enhance results of multiple sequence alignment by hand. QAlign combines algorithms for fast progressive and accurate simultaneous multiple alignment with a versatile editor and a dynamic phylogenetic analysis in a convenient graphical user interface.

• REPuter: the manifold applications of repeat analysis on a genomic scale.

  Authors: S Kurtz, J V Choudhuri, E Ohlebusch, C Schleiermacher, J Stoye, R Giegerich

  Nucleic acids research. 12/2001; 29(22):4633-42.

  The repetitive structure of genomic DNA holds many secrets to be discovered. A systematic study of repetitive DNA on a genomic or inter-genomic scale requires extensive algorithmic support. TheThe repetitive structure of genomic DNA holds many secrets to be discovered. A systematic study of repetitive DNA on a genomic or inter-genomic scale requires extensive algorithmic support. The REPuter program described herein was designed to serve as a fundamental tool in such studies. Efficient and complete detection of various types of repeats is provided together with an evaluation of significance and interactive visualization. This article circumscribes the wide scope of repeat analysis using applications in five different areas of sequence analysis: checking fragment assemblies, searching for low copy repeats, finding unique sequences, comparing gene structures and mapping of cDNA/EST sequences.

• Computation and visualization of degenerate repeats in complete genomes.

  Authors: S Kurtz, E Ohlebusch, C Schleiermacher, J Stoye, R Giegerich

  Proceedings / ... International Conference on Intelligent Systems for Molecular Biology ; ISMB. International Conference on Intelligent Systems for Molecular Biology. 02/2000; 8:228-38.

  The repetitive structure of genomic DNA holds many secrets to be discovered. A systematic study of repetitive DNA on a genomic or inter-genomic scale requires extensive algorithmic support. TheThe repetitive structure of genomic DNA holds many secrets to be discovered. A systematic study of repetitive DNA on a genomic or inter-genomic scale requires extensive algorithmic support. The REPuter family of programs described herein was designed to serve as a fundamental tool in such studies. Efficient and complete detection of various types of repeats is provided together with an evaluation of significance, interactive visualization, and simple interfacing to other analysis programs.

• Divide-and-Conquer Multiple Sequence Alignment

  Authors: Universitt Bielefeld, J. Stoye, S. W. Perrey, A. W. M. Dress

  01/2000;

  dvantage of this fact by rst dividing s1 at its midpoint ^ c1 := djs 1 j=2e and then searching for compatible positions in the other sequences. To estimate the compatibility of slicing positions c, ddvantage of this fact by rst dividing s1 at its midpoint ^ c1 := djs 1 j=2e and then searching for compatible positions in the other sequences. To estimate the compatibility of slicing positions c, d of sequences s, t, we dene the additional cost C s;t [c; d] imposed by rst slicing s and t at c and d, respectively, and then aligning s and t by concatenating the optimal alignments of the resulting prex and sux sequences by C s;t [c; d] := w opt (prex) + w opt (sux) w opt (total) w

• Multiple sequence alignment with the Divide-and-Conquer method.

  Authors: J. Stoye

  Gene. 06/1998; 211(2):GC45-56.

  An improved algorithm for the simultaneous alignment of multiple protein and nucleic acid sequences, the Divide-and-Conquer Alignment procedure (DCA), is presented. The basic method described inAn improved algorithm for the simultaneous alignment of multiple protein and nucleic acid sequences, the Divide-and-Conquer Alignment procedure (DCA), is presented. The basic method described in Tönges,et al. (1996) (Tönges, U., Perrey, S.W., Stoye, J., Dress, A.W.M., 1996. A general method for fast multiple sequence alignment. Gene, 172, GC33-GC41) is generalized to align any number of sequences to work arbitrary (e.g. affine linear) gap penalty functions. Also, the practical efficiency of the method is improved so that families of more than 10 sequences can now be aligned simultaneously within a few seconds or minutes. After a brief description of the general method, we assess the time and memory requirements of our implementation of DCA. We present several examples showing that the program is able to deal with real-world alignment problems.

• DCA: an efficient implementation of the divide-and-conquer approach to simultaneous multiple sequence alignment.

  Authors: J. Stoye, V. Moulton, A W Dress

  Computer applications in the biosciences : CABIOS. 01/1998; 13(6):625-6.

  MOTIVATION: DCA is a new computer program for multiple sequence alignment which utilizes a 'divide-and-conquer' type of heuristic approach. AVAILABILITY: The algorithm is freely available fromMOTIVATION: DCA is a new computer program for multiple sequence alignment which utilizes a 'divide-and-conquer' type of heuristic approach. AVAILABILITY: The algorithm is freely available from http://bibiserv.TechFak.Uni-Bielefeld.DE/dca/.

• Rose: generating sequence families.

  Authors: J. Stoye, D Evers, F Meyer

  Bioinformatics (Oxford, England). 01/1998; 14(2):157-63.

  We present a new probabilistic model of the evolution of RNA-, DNA-, or protein-like sequences and a software tool, Rose, that implements this model. Guided by an evolutionary tree, a family ofWe present a new probabilistic model of the evolution of RNA-, DNA-, or protein-like sequences and a software tool, Rose, that implements this model. Guided by an evolutionary tree, a family of related sequences is created from a common ancestor sequence by insertion, deletion and substitution of characters. During this artificial evolutionary process, the 'true' history is logged and the 'correct' multiple sequence alignment is created simultaneously. The model also allows for varying rates of mutation within the sequences, making it possible to establish so-called sequence motifs. The data created by Rose are suitable for the evaluation of methods in multiple sequence alignment computation and the prediction of phylogenetic relationships. It can also be useful when teaching courses in or developing models of sequence evolution and in the study of evolutionary processes. Rose is available on the Bielefeld Bioinformatics WebServer under the following URL: http://bibiserv.TechFak.Uni-Bielefeld.DE/rose/ The source code is available upon request. Contact: folker@TechFak.Uni-Bielefeld.DE

• Two Applications of the Divide Conquer Principle in the Molecular Sciences

  Authors: Forschungsschwerpunkt Mathematisierung, G. Brinkmann, A. W. M. Dress, S. W. Perrey, J. Stoye

  08/1997;

  In this note, two problems from the molecular sciences are addressed: the enumeration of fullerene-type isomers and the alignment of biosequences. We report on two algorithms dealing with theseIn this note, two problems from the molecular sciences are addressed: the enumeration of fullerene-type isomers and the alignment of biosequences. We report on two algorithms dealing with these problems both of which are based on the well-known and widely used Divide &Conquer principle. In other words, our algorithms attack the original problems by associating with them an appropriate number of much simpler problems whose solutions can be "glued together" to yield solutions of the original, rather complex tasks. The considerable improvements achieved this way exemplify that the present day molecular sciences offer many worthwhile opportunities for the effective use of fundamental algorithmic principles and architectures. 3 1 Introduction One of the most powerful principles for solving complex tasks algorithmically is the so-called Divide&Conquer Principle. It has been applied successfully for an amazingly wide range of problems, from combinatorial optimization to matrix mu...

• Improving the Divide-and-Conquer Approach to Sum-of-Pairs Multiple Sequence Alignment

  Authors: J. Stoye, S. W. Perrey, A. W. M. Dress

  06/1997;

  We consider the problem of multiple sequence alignment: given k sequences of length at most n and a certain scoring function, find an alignment that minimizes the corresponding "sum of pairs"We consider the problem of multiple sequence alignment: given k sequences of length at most n and a certain scoring function, find an alignment that minimizes the corresponding "sum of pairs" distance score. We generalize the divide-and-conquer technique described in [1,2], and present new ideas on how to use efficient search strategies for saving computer memory and accelerating the procedure for three or more sequences. Resulting running times and memory usage are shown for several test cases. Keywords---Multiple sequence alignment, Dynamic programming, Divide-and-conquer. 1. INTRODUCTION Multiple sequence alignment is an important problem in computational molecular biology, and many algorithms have been presented in this area of research (for a recent comparison see [3]). Since the problem of computing optimal alignments with respect to the "sum-of-pairs" criterion and most of its variants are NP-hard [4], many approximative algorithms have been proposed (e.g., [5--8]), Unfo...

• Generating benchmarks for multiple sequence alignments and phylogenetic reconstructions.

  Authors: J. Stoye, D Evers, F Meyer

  Proceedings / ... International Conference on Intelligent Systems for Molecular Biology ; ISMB. International Conference on Intelligent Systems for Molecular Biology. 02/1997; 5:303-6.

  We present a new probabilistic model of evolution of RNA-, DNA-, or protein-like sequences and a tool rose that implements this model. By insertion, deletion and substitution of characters, a familyWe present a new probabilistic model of evolution of RNA-, DNA-, or protein-like sequences and a tool rose that implements this model. By insertion, deletion and substitution of characters, a family of sequences is created from a common ancestor. During this artificial evolutionary process, the "true" history is logged and the "correct" multiple sequence alignment is created simultaneously. We also allow for varying rates of mutation within the sequences making it possible to establish so-called sequence motifs. The results are suitable for the evaluation of methods in multiple sequence alignment computation and the prediction of phylogenetic relationships.

• A general method for fast multiple sequence alignment.

  Authors: U Tönges, S. W. Perrey, J. Stoye, A W Dress

  Gene. 07/1996; 172(1):GC33-41.

  We have developed a fast heuristic algorithm for multiple sequence alignment which provides near-to-optimal results for sufficiently homologous sequences. The algorithm makes use of the standardWe have developed a fast heuristic algorithm for multiple sequence alignment which provides near-to-optimal results for sufficiently homologous sequences. The algorithm makes use of the standard dynamic programming procedure by applying it to all pairs of sequences. The resulting score matrices for pair-wise alignment give rise to secondary matrices containing the additional charges imposed by forcing the alignment path to run through a particular vertex. Such a constraint corresponds to slicing the sequences at the positions defining that vertex, and aligning the remaining pairs of prefix and suffix sequences separately. From these secondary matrices, one can compute-for any given family of sequences-suitable positions for cutting all of these sequences simultaneously, thus reducing the problem of aligning a family of n sequences of average length l in a Divide and Conquer fashion to aligning two families of n sequences of approximately half that length. In this paper, we explain the method for the case of 3 sequences in detail, and we demonstrate its potential and its limits by discussing its behaviour for several test families. A generalization for aligning more than 3 sequences is lined out, and some actual alignments constructed by our algorithm for various user-defined parameters are presented.

• On Simultaneous versus Iterative Multiple Sequence Alignment

  Authors: Forschungsschwerpunkt Mathematisierung, S. W. Perrey, J. Stoye, V. Moulton, A. W. M. Dress

  02/1970;

  One of the main problems in computational biology is the construction of biologically plausible alignments for given sequence families. Many procedures have been developed for this purpose; most areOne of the main problems in computational biology is the construction of biologically plausible alignments for given sequence families. Many procedures have been developed for this purpose; most are based on clustering the sequences hierarchically prior to the computation of their alignment and then proceeding recursively. In this paper, we compare results obtained with a new algorithm for simultaneous multiple sequence alignment, the so-called Divide & Conquer Alignment procedure (DCA), with results obtained with iterative procedures. DCA allows one to simultaneously align relatively large families of sequences using computationally efficient heuristics which -- relative to the sum-of-pairs scoring function which DCA accepts as the standard of truth -- give rise to good (though not necessarily optimal) alignments. As expected, the simultaneous alignments often prove superior in picking up biologically important signals contained in a family of highly diverged sequences, ...

• Improving the divide-and-conquer approach to sum-of-pairs multiple sequence alignment

  Authors: J. Stoye, S.W. Perrey, A.W.M. Dress

  Applied Mathematics Letters.

  We consider the problem of multiple sequence alignment: given k sequences of length at most n and a certain scoring function, find an alignment that minimizes the corresponding “sum of pairs”We consider the problem of multiple sequence alignment: given k sequences of length at most n and a certain scoring function, find an alignment that minimizes the corresponding “sum of pairs” distance score.We generalize the divide-and-conquer technique described in [1,2], and present new ideas on how to use efficient search strategies for saving computer memory and accelerating the procedure for three or more sequences. Resulting running times and memory usage are shown for several test cases.