Sentence examples for multiple related genomes from inspiring English sources

We describe a new and flexible framework for modeling binding site evolution in multiple related genomes, based on phylogenetic pair hidden Markov models which explicitly model the gain and loss of binding sites along a phylogeny.

Does the availability of multiple related genomes foster or complicate CRM detection?

Although a direct comparison is not fair we will see in the next experiment that the use of multiple related genomes as reference sequences improves the resulting layouts.

We demonstrated that with multiple related genomes available, one can obtain a complete and high-quality scaffold for each chromosome using only high-throughput short-read sequencing.

We introduce an assembly integrator that makes use of all available data, i.e. multiple de novo assemblies and mappings against multiple related genomes, by optimizing a weighted combination of criteria.

To address the problem of inferring consistent chromatin state definition across multiple related genomes, we employ an infinite HMM (iHMM) (Beal et al., 2002), a non-parametric extension of a finite state HMM, as a base model and extend it to model data from multiple conditions.

However, PCR amplification and sequencing of amplicons from 8 of 9 single pHap families presented evidence of multiple related sequences in the genome of Williams 82.

Some publications report data from multiple related experiments, such as genome-wide chromatin immunoprecipitation assays (i.e. ChIP-chip, ChIP-seq) that can be grouped and displayed as subtracks, allowing for toggling of track display by experimental attributes such as the binding factor of interest and growth conditions.

With the easy acquisition of sequence data, it is now possible to obtain and align whole genomes across multiple related species or populations.

Genome scans across multiple related species along climate gradients are likely to provide many other examples of candidate genomic regions associated with climate adaptation and exchanged through hybridization and introgression.

GFlasso is a sparse multivariate regression method that we have previously developed for finding a correlated genome association for multiple related traits given a trait network and genotype/phenotype dataset [ 7].