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Titlebook: Research in Computational Molecular Biology; 14th Annual Internat Bonnie Berger Conference proceedings 2010 Springer-Verlag Berlin Heidelbe

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An Algorithmic Framework for Predicting Side-Effects of Drugs,nts aimed at discovering such side effects are very costly and may miss subtle or rare side effects. To date, and to the best of our knowledge, no computational approach was suggested to systematically tackle this challenge. In this work we report on a novel approach to predict the side effects of a
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Pathway-Based Functional Analysis of Metagenomes, analysis of metagenomes explores the abundance of gene families, pathways, and systems, rather than their taxonomy. Through such analysis researchers are able to identify those functional capabilities most important to organisms in the examined environment. Recently, a statistical framework for the
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Hierarchical Generative Biclustering for MicroRNA Expression Analysis,indicator of which genes tie each cluster, changing the setup to biclustering. Furthermore, we make the indicators hierarchical, resulting in a hierarchy of progressively more specific biclusters. A non-parametric Bayesian formulation makes the model rigorous and yet flexible, and computations feasi
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Subnetwork State Functions Define Dysregulated Subnetworks in Cancer,ntification of interacting proteins that are coordinately dysregulated in tumorigenic and metastatic samples. When used as features for classification, such coordinately dysregulated subnetworks improve diagnosis and prognosis of cancer considerably over single-gene markers. However, existing method
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Proteome Coverage Prediction for Integrated Proteomics Datasets,xture, i.e. to identify as many proteins as possible, various different fractionation experiments are typically performed and the individual fractions are subjected to mass spectrometric analysis. The resulting data are integrated into large and heterogeneous datasets. Proteome coverage prediction r
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Discovering Regulatory Overlapping RNA Transcripts,rom tiling expression data. . first identifies coherent segments of transcription and then discovers individual transcripts that are consistent with the observed segments given intensity and shape constraints. We used . to identify 1446 regions of overlapping transcription in two strains of yeast, i
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