Titlebook: Research in Computational Molecular Biology; 17th Annual Internat Minghua Deng,Rui Jiang,Xuegong Zhang Conference proceedings 2013 Springer

paltry

Assembling Genomes and Mini-metagenomes from Highly Chimeric Reads,bacteria. However, single-cell assembly projects are challenging due to (i) the highly non-uniform read coverage, and (ii) a greatly elevated number of chimeric reads and read pairs. While recently developed single-cell assemblers have addressed the former challenge, methods for assembling highly ch

Essential

Inferring Intra-tumor Heterogeneity from High-Throughput DNA Sequencing Data,ncerous cells in a tumor are descended from a single founder cell and that descendants of this cell acquired multiple mutations beneficial for tumor growth through rounds of selection and . expansion. A tumor is thus a heterogeneous population of cells, with different subpopulations of cells contain

incisive

NP-MuScL: Unsupervised Global Prediction of Interaction Networks from Multiple Data Sources,urce. However, in many real world applications, multiple data sources, such as microarray and ISH measurements of mRNA abundances, are available to offer multi-view information about the same set of genes. We propose NP-MuScL (nonparanormal multi-source learning) to estimate a gene interaction netwo

Ingrained

效果

Diuretic

An Accurate Method for Inferring Relatedness in Large Datasets of Unphased Genotypes via an Embedde For example, in genome-wide association studies, the cohort members are assumed to be unrelated to one another. Investigators can correct for individuals in a cohort with previously-unknown shared familial descent by detecting genomic segments that are shared between them, which are considered to b

躲債

MARS

小官

Reconciliation Revisited: Handling Multiple Optima When Reconciling with Duplication, Transfer, andfficiently sample the space of optimal reconciliations uniformly at random in .(..) time, where . and . denote the number of genes and species, respectively. We use these samples to understand how different optimal reconciliations vary in their node mapping and event assignments, and to investigate the impact of varying event costs.

存心

Dissecting Cancer Heterogeneity with a Probabilistic Genotype-Phenotype Model, of the subtypes that best explain the patient similarity network. Our approach does not assume predefined subtypes nor does it assume that such subtypes have to be uniquely defined. That is, we do not assume that there exist “the” disease subtype model but rather we consider a distribution of such models providing a probabilistic context.