Auflistung P071 - GCB 2005 - German Conference on Bioinformatics nach Erscheinungsdatum
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- KonferenzbeitragPlanning isotopomer measurements for estimation of metabolic fluxes(German Conference on Bioinformatics 2005 (GCB 2005), 2005) Rantanen, Ari; Mielikäinen, Taneli; Rousu, Juho; Ukkonen, EskoFlux estimation by using isotopomer information of metabolites is currently the only method that can give quantitative estimates of the activity of metabolic pathways. However, the measurement of isotopomer distributions of intermediate metabolites is costly and tedious with current technologies. In this paper we study the question of finding the smallest subset of metabolites to measure that ensure an adequate level of the isotopomer information. We study the computational complexity of this optimization problem in the case of the so-called positional enrichment data, give exact and fast heuristic solutions and evaluate empirically the efficacy of the proposed methods.
- KonferenzbeitragData processing effects on the interpretation of microarray gene expression experiments(German Conference on Bioinformatics 2005 (GCB 2005), 2005) Fundel, Katrin; Küffner, Robert; Aigner, Thomas; Zimmer, RalfMotivation: Microarray gene expression data is collected at an increasing pace and numerous methods and tools exist for analyzing this kind of data. The aim of this study is to evaluate the effect of the basic statistical processing steps of microarray data on the final outcome for gene expression analysis; these effects are most problematic for one-channel cDNA measurements, but also affect other types of microarrays, especially when dealing with grouped samples. It is crucial to determine an appropriate combination of individual processing steps for a given dataset in order to improve the validity and reliability of expression data analysis. Results: We analyzed a large gene expression data set obtained from a one-channel cDNA microarray experiment conducted on 83 human samples that have been classified into four Osteoarthritis related groups. We compared different normalization methods regarding the effect on the identification of differentially expressed genes. Furthermore, we compared different methods for combining spot p-values into gene p-values, and propose Stouffer's method for this purpose. We developed several quality and robustness measures which allow to estimate the amount of errors made in the statistical data preparation. Conclusion: The apparently straight forward steps of gene expression data analysis, i.e. normalization and identification of differentially expressed genes, can be accomplished by numerous different methods. We analyzed multiple combinations of a number of methods to demonstrate the possible effects and therefore the importance of the single decisions taken during data processing. An overview of these effects is essential for the biological interpretation of gene expression measurements. We give guidelines and tools for evaluating methods for normalization, spot combination and detection of differentially regulated genes.
- KonferenzbeitragEfficient mapping of large cDNA/EST databases to genomes: A comparison of two different strategies(German Conference on Bioinformatics 2005 (GCB 2005), 2005) Wawra, Christian; Abouelhoda, Mohamed I.; Ohlebusch, EnnoThis paper presents a comparison of two strategies for cDNA/EST mapping: The seed-and-extend strategy and the fragment-chaining strategy. We derive theoretical results on the statistics of fragments of type maximal exact match. Moreover, we present efficient fragment-chaining algorithms that are simpler than previous ones. In experiments, we compared our implementation of the fragment-chaining strategy with the seed-and-extend strategy implemented in the software tool BLAT.
- Editiertes Buch
- 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.
- KonferenzbeitragUsing N-terminal targeting sequences, amino acid composition, and sequence motifs for predicting protein subcellular localization(German Conference on Bioinformatics 2005 (GCB 2005), 2005) Höglund, Annette; Dönnes, Pierre; Blum, Torsten; Adolph, Hans-Werner; Kohlbacher, OliverFunctional annotation of unknown proteins is a major goal in proteomics. A key step in this annotation process is the definition of a protein's subcellular localization. As a consequence, numerous prediction techniques for localization have been developed over the years. These methods typically focus on a single underlying biological aspect or predict a subset of all possible subcellular localizations. There is a clear need for new methods that utilize and represent available protein specific biological knowledge from several sources, in order to improve accuracy and localization coverage for a wide range of organisms. Here we present a novel Support Vector Machine (SVM)-based approach for predicting protein subcellular localization, which integrates information about N-terminal targeting sequences, amino acid composition, and protein sequence motifs. An important step is taken towards emulating the protein sorting process by capturing and bringing together biologically relevant information. Our novel approach has been used to develop two new prediction methods, TargetLoc and MultiLoc. TargetLoc is restricted to analysis of proteins containing N-terminal targeting sequences, whereas MultiLoc covers all major eukaryotic subcellular localizations for animal, plant, and fungal proteins. Compared to similar methods, TargetLoc performs better than these. MultiLoc performs considerably better than comparable prediction methods predicting all major eukaryotic subcellular localizations, and shows better or comparable results to methods that are specialized on fewer localizations or for one organism.
- KonferenzbeitragInvited talk: Landscapes in RNA folding and evolution(German Conference on Bioinformatics 2005 (GCB 2005), 2005) Schuster, Peter
- KonferenzbeitragExploiting scale-free information from expression data for cancer classification(German Conference on Bioinformatics 2005 (GCB 2005), 2005) Antonov, Alexey V.; Tetko, Igor V.; Kosykh, Denis; Surmeli, Dmitrij; Mewes, Hans-WernerIn most studies concerning expression data analyses information on the variability of gene intensity across samples is usually exploited. This information is sensitive to initial data processing which affects the final conclusions. However expression data contains scale free information which is directly comparable between different samples. We propose to use the pairwise ratio of gene expression values rather than their absolute intensities for classification of expression data. This information is stable to data processing and thus more attractive for classification analyses. In proposed schema of data analyses only information on relative gene expression levels in each sample is exploited. Testing on publicly available datasets leads to superior classification results.
- KonferenzbeitragFamily specific rates of protein evolution(German Conference on Bioinformatics 2005 (GCB 2005), 2005) Luz, Hannes; Vingron, MartinAmino acid changing mutations in proteins are contstrained by purifying selection and accumulate at different rates. We estimate evolutionary rates on multiple alignments of eukaryotic protein families in a maximum likelihood framework. We find that the evolution of indispensable proteins is constrained by selection and that protein secretion is coupled to an increased evolutionary rate.
- KonferenzbeitragInvited talk: A large-scale application of comparative genomics for biodefense(German Conference on Bioinformatics 2005 (GCB 2005), 2005) Slezak, Tom
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