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Titlebook: Research in Computational Molecular Biology; 21st Annual Interna S. Cenk Sahinalp Conference proceedings 2017 Springer International Publi

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Boosting Alignment Accuracy by Adaptive Local Realignment,ng-function parameters across a protein’s entire length. We present a new approach, called ., that in contrast automatically adapts to the diversity of mutation rates along protein sequences. This builds upon a recent technique known as parameter advising that finds global parameter settings for ali
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A Concurrent Subtractive Assembly Approach for Identification of Disease Associated Sub-metagenomesost status). The typical workflow is to assemble and annotate metagenomic datasets individually or as a whole, followed by statistical tests to identify differentially abundant species/genes. We previously developed subtractive assembly (SA), a . assembly approach for comparative metagenomics that f
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Determining the Consistency of Resolved Triplets and Fan Triplets, that contains all elements in . and no elements in . as embedded subtrees, if such a tree exists. This paper presents a detailed characterization of how the computational complexity of the problem changes under various restrictions. Our main result is an efficient algorithm for dense inputs satisfy
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Progressive Calibration and Averaging for Tandem Mass Spectrometry Statistical Confidence EstimatioHere we offer two new methods that can use an arbitrarily small number of additional randomly drawn decoy databases to improve TDC. Specifically, “Partial Calibration” utilizes a new meta-scoring scheme that allows us to gradually benefit from the increase in the number of identifications calibratio
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Resolving Multicopy Duplications , Using Polyploid Phasing,segmental duplications in the genome still remain a challenging frontier in assembly. Segmental duplications are at the same time both gene rich and prone to large structural rearrangements, making the resolution of their sequences important in medical and evolutionary studies. Duplicated sequences
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A Bayesian Active Learning Experimental Design for Inferring Signaling Networks,ction networks. They provide insight into the rewiring of signaling within the context of a disease or a phenotype. To learn the causal patterns of influence between proteins in the network, the methods require experiments that include targeted interventions that fix the activity of specific protein
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