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Titlebook: Algorithms for Computational Biology; 4th International Co Daniel Figueiredo,Carlos Martín-Vide,Miguel A. Veg Conference proceedings 2017 S

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Inferring the Distribution of Fitness Effects (DFE) of Newly-Arising Mutations Using Samples Taken f
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Der Aufbau eines Superorganismus,nalysis to compare . to a state-of-art tool for spliced alignment (.), and to identify novel putative alternative splicing events such as exon skipping directly from mapping reads to the graph. Such analysis shows that our tool is able to perform accurate mapping of reads to exons, with good time an
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https://doi.org/10.1007/978-3-642-91406-5 TC score. Based on the results presented herein, CSA-X significantly outperforms RE-MuSiC. On average, CSA-X used with constraints that were algorithmically created from the least conserved regions of the correct alignments achieves results that are 17.65% higher for Q score, and 23.7% higher for T
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Biomedical Applications of Prototype Based Classifiers and Relevance LearningVector Quantization and Matrix Relevance Learning serve as the main examples. After introducing basic concepts and related approaches, example applications of Generalized Matrix Relevance Learning are reviewed, including the classification of adrenal tumors based on steroid metabolomics data, the an
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Describing the Local Structure of Sequence Graphsn open problem. Paten’s invention of the . and ., special subgraphs of sequence graphs which can identified with efficient algorithms, represents important first step to segregating graphs into genetic sites. We extend the theory of ultrabubbles to a special subclass where every detail of the ultrab
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Mapping RNA-seq Data to a Transcript Graph via Approximate Pattern Matching to a Hypertextxt, that is a graph where nodes are texts representing the exons of the gene and edges connect consecutive exons of a transcript. Mapping reads obtained by deep transcriptome sequencing to such graphs is crucial to compare reads with an annotation of transcript isoforms and to infer novel events due
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Ranking Vertices for Active Module Recovery Problemnalysis of gene expression data, mutations, metabolomic profiles and others. It can be formulated as a recovery of an active module from which an experimental signal is generated. Commonly, methods for solving this problem result in a single subnetwork that is considered to be a good candidate. Howe
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Computational Processes that Appear to Model Human Memorys thought that . models long-term memory consolidation and . models memory recall. A derived, intermediate network form, consisting of chordless cycles, could be the structural substrate of long-term memory; just as the double helix is the necessary substrate for genomic memory.
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An Efficient Algorithm for the Rooted Triplet Distance Between Galled Treese vertex-disjoint) runs in . time, where . is the cardinality of the leaf label set. Here, we present an .-time solution. Our strategy is to transform the input so that the answer can be obtained by applying an existing .-time algorithm for the simpler case of two phylogenetic trees a constant numbe
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