Biomedical subjects

Jens Stoye

Publications and source records attributed to Jens Stoye.

13 recordsLinked to original sources

PubMed2006

GISMO--gene identification using a support vector machine for ORF classification.

We present the novel prokaryotic gene finder GISMO, which combines searches for protein family domains with composition-based classification based on a support vector machine. GISMO is highly accurate; exhibiting high sensitivity and specificity in gene identification. We found that it performs well for complete prokaryotic chromosomes, irrespective of their GC content, and also for plasmids as short as 10 kb, short genes and for genes with atypical sequence composition. Using GISMO, we found several thousand new predictions for the published genomes that are supported by extrinsic evidence, which strongly suggest that these are very likely biologically active genes. The source code for GISMO is freely available under the GPL license.

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PubMed2006

Finding novel genes in bacterial communities isolated from the environment.

MOTIVATION: Novel sequencing techniques can give access to organisms that are difficult to cultivate using conventional methods. When applied to environmental samples, the data generated has some drawbacks, e.g. short length of assembled contigs, in-frame stop codons and frame shifts. Unfortunately, current gene finders cannot circumvent these difficulties. At the same time, the automated prediction of genes is a prerequisite for the increasing amount of genomic sequences to ensure progress in metagenomics. RESULTS: We introduce a novel gene finding algorithm that incorporates features overcoming the short length of the assembled contigs from environmental data, in-frame stop codons as well as frame shifts contained in bacterial sequences. The results show that by searching for sequence similarities in an environmental sample our algorithm is capable of detecting a high fraction of its gene content, depending on the species composition and the overall size of the sample. The method is valuable for hunting novel unknown genes that may be specific for the habitat where the sample is taken. Finally, we show that our algorithm can even exploit the limited information contained in the short reads generated by 454 technology for the prediction of protein coding genes. AVAILABILITY: The program is freely available upon request.

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PubMed2006

Panta rhei (QAlign2): an open graphical environment for sequence analysis.

MOTIVATION: The first version of the graphical multiple sequence alignment environment QAlign was published in 2003. Heavy response from the molecular-biological user community clearly demonstrated the need for such a platform. RESULTS: Panta rhei extends QAlign by several features. Major redesigns on the user interface, for instance, allow users to flexibily compose views for multiple projects. The new sequence viewer handles datasets with arbitrarily many and arbitrarily large sequences that may still be edited by guided block moving. More distance-based algorithms are available to interactively reconstruct phylogenetic trees which can now also be zoomed and navigated graphicaly. AVAILABILITY: Executables and the JAVA source code are available under the Apache license at http://gi.cebitec.uni-bielefeld.de/qalign CONTACT: qalign@cebitec.uni-bielefeld.de.

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PubMed2006

On the similarity of sets of permutations and its applications to genome comparison.

The comparison of genomes with the same gene content relies on our ability to compare permutations, either by measuring how much they differ, or by measuring how much they are alike. With the notable exception of the breakpoint distance, which is based on the concept of conserved adjacencies, measures of distance do not generalize easily to sets of more than two permutations. In this paper, we present a basic unifying notion, conserved intervals, as a powerful generalization of adjacencies, and as a key feature of genome rearrangement theories. We also show that sets of conserved intervals have elegant nesting and chaining properties that allow the development of compact graphic representations, and linear time algorithms to manipulate them.

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PubMed2006

Efficient q-gram filters for finding all epsilon-matches over a given length.

Fast and exact comparison of large genomic sequences remains a challenging task in biosequence analysis. We consider the problem of finding all epsilon-matches between two sequences, i.e., all local alignments over a given length with an error rate of at most epsilon. We study this problem theoretically, giving an efficient q-gram filter for solving it. Two applications of the filter are also discussed, in particular genomic sequence assembly and BLAST-like sequence comparison. Our results show that the method is 25 times faster than BLAST, while not being heuristic.

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PubMed2006

On sorting by translocations.

The study of genome rearrangements is an important tool in comparative genomics. This paper revisits the problem of sorting a multichromosomal genome by translocations, i.e., exchanges of chromosome ends. We give an elementary proof of the formula for computing the translocation distance in linear time, and we give a new algorithm for sorting by translocations, correcting an error in a previous algorithm by Hannenhalli.

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PubMed2005

Large scale hierarchical clustering of protein sequences.

BACKGROUND: Searching a biological sequence database with a query sequence looking for homologues has become a routine operation in computational biology. In spite of the high degree of sophistication of currently available search routines it is still virtually impossible to identify quickly and clearly a group of sequences that a given query sequence belongs to. RESULTS: We report on our developments in grouping all known protein sequences hierarchically into superfamily and family clusters. Our graph-based algorithms take into account the topology of the sequence space induced by the data itself to construct a biologically meaningful partitioning. We have applied our clustering procedures to a non-redundant set of about 1,000,000 sequences resulting in a hierarchical clustering which is being made available for querying and browsing at http://systers.molgen.mpg.de/. CONCLUSIONS: Comparisons with other widely used clustering methods on various data sets show the abilities and strengths of our clustering methods in producing a biologically meaningful grouping of protein sequences.

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PubMed2004

BACCardI--a tool for the validation of genomic assemblies, assisting genome finishing and intergenome comparison.

SUMMARY: We provide the graphical tool BACCardI for the construction of virtual clone maps from standard assembler output files or BLAST based sequence comparisons. This new tool has been applied to numerous genome projects to solve various problems including (a) validation of whole genome shotgun assemblies, (b) support for contig ordering in the finishing phase of a genome project, and (c) intergenome comparison between related strains when only one of the strains has been sequenced and a large insert library is available for the other. The BACCardI software can seamlessly interact with various sequence assembly packages. MOTIVATION: Genomic assemblies generated from sequence information need to be validated by independent methods such as physical maps. The time-consuming task of building physical maps can be circumvented by virtual clone maps derived from read pair information of large insert libraries.

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PubMed2004

Benchmarking tools for the alignment of functional noncoding DNA.

BACKGROUND: Numerous tools have been developed to align genomic sequences. However, their relative performance in specific applications remains poorly characterized. Alignments of protein-coding sequences typically have been benchmarked against "correct" alignments inferred from structural data. For noncoding sequences, where such independent validation is lacking, simulation provides an effective means to generate "correct" alignments with which to benchmark alignment tools. RESULTS: Using rates of noncoding sequence evolution estimated from the genus Drosophila, we simulated alignments over a range of divergence times under varying models incorporating point substitution, insertion/deletion events, and short blocks of constrained sequences such as those found in cis-regulatory regions. We then compared "correct" alignments generated by a modified version of the ROSE simulation platform to alignments of the simulated derived sequences produced by eight pairwise alignment tools (Avid, BlastZ, Chaos, ClustalW, DiAlign, Lagan, Needle, and WABA) to determine the off-the-shelf performance of each tool. As expected, the ability to align noncoding sequences accurately decreases with increasing divergence for all tools, and declines faster in the presence of insertion/deletion evolution. Global alignment tools (Avid, ClustalW, Lagan, and Needle) typically have higher sensitivity over entire noncoding sequences as well as in constrained sequences. Local tools (BlastZ, Chaos, and WABA) have lower overall sensitivity as a consequence of incomplete coverage, but have high specificity to detect constrained sequences as well as high sensitivity within the subset of sequences they align. Tools such as DiAlign, which generate both local and global outputs, produce alignments of constrained sequences with both high sensitivity and specificity for divergence distances in the range of 1.25-3.0 substitutions per site. CONCLUSION: For species with genomic properties similar to Drosophila, we conclude that a single pair of optimally diverged species analyzed with a high performance alignment tool can yield accurate and specific alignments of functionally constrained noncoding sequences. Further algorithm development, optimization of alignment parameters, and benchmarking studies will be necessary to extract the maximal biological information from alignments of functional noncoding DNA.

Animals↗

PubMed2003

The European conference on computational biology.

Highlights from the first European Conference on Computational Biology (ECCB 2002), held in conjunction with the German Conference on Bioinformatics (GCB 2002), 6-9 October 2002, Saarbrücken, Germany.

Computational Biology↗

PubMed2003

Divide-and-conquer multiple alignment with segment-based constraints.

A large number of methods for multiple sequence alignment are currently available. Recent benchmarking tests demonstrated that strengths and drawbacks of these methods differ substantially. Global strategies can be outperformed by approaches based on local similarities and vice versa, depending on the characteristics of the input sequences. In recent years, mixed approaches that include both global and local features have shown promising results. Herein, we introduce a new algorithm for multiple sequence alignment that integrates the global divide-and-conquer approach with the local segment-based approach, thereby combining the strengths of those two strategies.

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PubMed2002

A novel approach to remote homology detection: jumping alignments.

We describe a new algorithm for protein classification and the detection of remote homologs. The rationale is to exploit both vertical and horizontal information of a multiple alignment in a well-balanced manner. This is in contrast to established methods such as profiles and profile hidden Markov models which focus on vertical information as they model the columns of the alignment independently and to family pairwise search which focuses on horizontal information as it treats given sequences separately. In our setting, we want to select from a given database of "candidate sequences" those proteins that belong to a given superfamily. In order to do so, each candidate sequence is separately tested against a multiple alignment of the known members of the superfamily by means of a new jumping alignment algorithm. This algorithm is an extension of the Smith-Waterman algorithm and computes a local alignment of a single sequence and a multiple alignment. In contrast to traditional methods, however, this alignment is not based on a summary of the individual columns of the multiple alignment. Rather, the candidate sequence is at each position aligned to one sequence of the multiple alignment, called the "reference sequence." In addition, the reference sequence may change within the alignment, while each such jump is penalized. To evaluate the discriminative quality of the jumping alignment algorithm, we compare it to profiles, profile hidden Markov models, and family pairwise search on a subset of the SCOP database of protein domains. The discriminative quality is assessed by median false positive counts (med-FP-counts). For moderate med-FP-counts, the number of successful searches with our method is considerably higher than with the competing methods.

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PubMedDate not supplied

Comparing tandem repeats with duplications and excisions of variable degree.

Traditional sequence comparison by alignment employs a mutation model comprised of two events, substitutions and indels (insertions or deletions) of single positions. However, modern genetic analysis knows a variety of more complex mutation events (e.g., duplications, excisions, and rearrangements), especially regarding DNA. With ever more DNA sequence data becoming available, the need to accurately compare sequences which have clearly undergone more complicated types of mutational processes is becoming critical. Herein we introduce a new method for pairwise alignment and comparison of sequences with respect to the special evolution of tandem repeats: substitutions and indels of single positions and, additionally, duplications and excisions of variable degree (i.e., of one or more repeat copies simultaneously) are taken into account. To evaluate our method, we apply it to the spa VNTR (variable number of tandem repeats) cluster of Staphylococcus aureus, a bacterium of high medical importance.

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