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Titlebook: Algorithms for Computational Biology; 7th International Co Carlos Martín-Vide,Miguel A. Vega-Rodríguez,Travis Conference proceedings 2020 S

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BOAssembler: A Bayesian Optimization Framework to Improve RNA-Seq Assembly Performancepproach is effective to improve the overall assembly performance. The approach would be helpful for downstream (e.g. gene, protein, cell) analysis, and more broadly, for future bioinformatics benchmark studies.. ..
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https://doi.org/10.1007/978-3-658-33799-5rved haplotype blocks to pangenomes, which can store more complex variation than a single reference genome. We define a . and give a linear-time, suffix tree based approach to find all such blocks from a set of pangenome haplotypes. We demonstrate the method by applying it to a pangenome built from yeast strains.
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https://doi.org/10.1007/978-3-658-33799-5f combining networks into another network with low complexity. We characterize this complexity via a restricted problem, ., and we present an FPT algorithm to efficiently solve this restricted problem.
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https://doi.org/10.1007/978-3-8349-6980-4 on likelihoods of directed acyclic graphs. This algorithm is applied to transcript abundance data collected from . genes. This study extends the underlying statistical and mathematical theory of the Norris-Patton likelihood by including time series adjustments.
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Time Series Adjustment Enhancement of Hierarchical Modeling of , Gene Interactions on likelihoods of directed acyclic graphs. This algorithm is applied to transcript abundance data collected from . genes. This study extends the underlying statistical and mathematical theory of the Norris-Patton likelihood by including time series adjustments.
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