P115 - GCB 2007 - German Conference on Bioinformatics 2007
Auflistung P115 - GCB 2007 - German Conference on Bioinformatics 2007 nach Erscheinungsdatum
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- 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.
- KonferenzbeitragControl of translation: comparative genomics and mechanistic aspects(German conference on bioinformatics – GCB 2007, 2007) Pilpel, Yitzhak; Man, OrnaA major challenge in comparative genomics is to understand how phenotypic differences between species are encoded in their genomes. Phenotypic divergence may result from differential transcription of orthologous genes, yet less is known about the involvement of differential translation regulation in species phenotypic divergence. In order to assess translation effects on divergence, we analyzed approximately 2,800 orthologous genes in nine yeast genomes. For each gene in each species, we predicted translation efficiency, using a measure of the adaptation of its codons to the organism's tRNA pool. Mining this data set, we found hundreds of genes and gene modules with correlated patterns of translational efficiency across the species. One signal encompassed entire modules that are either needed for oxidative respiration or fermentation and are efficiently translated in aerobic or anaerobic species, respectively. In addition, the efficiency of translation of the mRNA splicing machinery strongly correlates with the number of introns in the various genomes. Altogether, we found extensive selection on synonymous codon usage that modulates translation according to gene function and organism phenotype. We conclude that, like factors such as transcription regulation, translation efficiency affects and is affected by the process of species divergence.
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- KonferenzbeitragInferring genomic footprints of adaptation from SNP data(German conference on bioinformatics – GCB 2007, 2007) Stephan, WolfgangAn important goal of population genetics is to determine the forces that have shaped the pattern of genetic variation in natural populations. For inferring the adaptive history of populations, we developed likelihood methods using the coalescent approach. We applied these techniques to Drosophila melanogaster, an originally African species that colonized temperate regions around the world after the last ice age. Our analyses suggest that the ancestral African population expanded its size about 60,000 years ago. The non-African populations split off from the African lineage about 16,000 years ago, thereby suffering severe population size bottlenecks. These demographic changes were accompanied by the fixation of numerous beneficial mutations, as revealed by signatures of positive directional selection in the genome (“selective sweeps”). The estimated rate of adaptive substitution is very high (in the order of one per genome per 100 generations). In several of the genomic regions exhibiting selective sweeps, we found genes with significant expression differences between African and non- African lines, suggesting that regulatory elements were the targets of selection and facilitated adaptation of fruit flies to temperate climates.
- KonferenzbeitragIdentifying microRNAs and their targets(German conference on bioinformatics – GCB 2007, 2007) Rajewsky, NikolausI will summarize what can be learned from predicting and analyzing microRNA targets. As an example, I will discuss the function of miR-150 in the immune system. Finally, I will present a new algorithm for the identification of microRNAs from deep sequencing data.
- KonferenzbeitragUnderstanding of SMFS barriers by means of energy profiles(German conference on bioinformatics – GCB 2007, 2007) Dressel, Frank; Marsico, Annalisa; Tuukkanen, Anne; Schroeder, Michael; Labudde, DirkIn the last years, Single Molecule Force Spectroscopy was more and more used to gain insight into the fundamental principles behind protein structure and stability. Nevertheless, the interpretation of the experimental findings is not so easy and additional computational approaches are needed to interpret them. Here, we proposed an approach based on interaction patterns between amino acids to explain the emergence of SMFS unfolding barriers in the experiment. With our approach, we can predict around 64% of the experimentally detectable barriers.
- KonferenzbeitragAn application of latent topic document analysis to large-scale proteomics databases(German conference on bioinformatics – GCB 2007, 2007) Klie, Sebastian; Martens, Lennart; Vizcaino, Juan Antonio; Cote, Richard; Jones, Phil; Apweiler, Rolf; Hinneburg, Alexander; Hermjakob, HenningSince the advent of public data repositories for proteomics data, readily accessible results from high-throughput experiments have been accumulating steadily. Several large-scale projects in particular have contributed substantially to the amount of identifications available to the community. Despite the considerable body of information amassed, very few successful analysis have been performed and published on this data, levelling off the ultimate value of these projects far below their potential. In order to illustrate that these repositories should be considered sources of detailed knowledge instead of data graveyards, we here present a novel way of analyzing the information contained in proteomics experiments with a ’latent semantic analysis’. We apply this information retrieval approach to the peptide identification data contributed by the Plasma Proteome Project. Interestingly, this analysis is able to overcome the fundamental difficulties of analyzing such divergent and heterogeneous data emerging from large scale proteomics studies employing a vast spec- trum of different sample treatment and mass-spectrometry technologies. Moreover, it yields several concrete recommendations for optimizing pro- teomics project planning as well as the choice of technologies used in the experiments. It is clear from these results that the analysis of large bodies of publicly available proteomics data holds great promise and is currently underexploited.
- KonferenzbeitragAre we overestimating the number of cell-cycling genes? The impact of background models for time series data(German conference on bioinformatics – GCB 2007, 2007) Futschik, Matthias E.; Herzel, HanspeterPeriodic processes play fundamental roles in organisms. Prominent examples are the cell cycle and the circadian clock. Microarray array technology has enabled us to screen complete sets of transcripts for possible association with such fundamental periodic processes on a system-wide level. Frequently, quite a large number of genes has been detected as periodically expressed. However, the small overlap of identified genes between different studies has shaded considerable doubts about the reliability of the detected periodic expression. In this study, we show that a major reason for the lacking agreement is the use of an inadequate background model for the determination of significance. We demonstrate that the choice of background model has considerable impact on the statistical significance of periodic expression. For illustration, we reanalyzed two microarray studies of the yeast cell cycle. Our evaluation strongly indicates that the results of previous analyses might have been overoptimistic and that the use of more suitable background model promises to give more realistic results.
- KonferenzbeitragProtein structure comparison based on fold evolution(German conference on bioinformatics – GCB 2007, 2007) Kurbatova, Natalja; Mančinska, Laura; Vīksna, JurisThe paper presents a protein structure comparison algorithm that is capable to identify specific fold mutations between two proteins. The search for such mutations is based on structure evolution models suggesting that, similarly as sequences, protein folds (at least partially) evolve by a stepwise process, where each step comprises comparatively simple changes affecting few secondary structure elements. The particular fold mutations considered in this study are based on the work by Grishin [Gr01]. The algorithm uses structure representation by 3D graphs and is a modification of a method used in SSM structure alignment tool [KH04a]. Experiments demonstrate that our method is able automatically identify 85% of examples of fold mutations given by Grishin. Also a number of tests involving all-against-all comparisons of CATH struc- tural domains have been performed in order to measure comparative frequencies of different types of fold mutations and some statistical estimations have been obtained.
- KonferenzbeitragA general paradigm for fast, adaptive clustering of biological sequences(German conference on bioinformatics – GCB 2007, 2007) Reinert, Knut; Bauer, Markus; Döring, Andreas; Klau, Gunnar W.; Halpern, Aaron L.There are numerous methods that compute clusterings of biological sequences based on pairwise distances. This necessitates the computation of O(n2) sequence comparisons. Users usually want to apply the most sensitive distance measure which normally is the most expensive in terms of runtime. This poses a problem if the number of sequences is large or the computation of the measure is slow. In this paper we present a general heuristic to speed up distance based clustering methods considerably while compromising little on the accuracy of the results. The speedup comes from using fast comparison methods to perform an initial ‘top-down’ split into relatively homogeneous clusters, while the slower measures are used for smaller groups. Then profiles are computed for the final groups and the resulting profiles are used in a bottom-up phase to compute the final clustering. The algorithm is general in the sense that any sequence comparison method can be employed (e.g. for DNA, RNA or amino acids). We test our algorithm using a prototypical imple- mentation for agglomerative RNA clustering and show its effectiveness.