Search Results for "high performance computing"

This package provides high-level interface utilities for MCMC models via Just Another Gibbs Sampler (JAGS), facilitating the use of parallel (or distributed) processors for multiple chains, automated control of convergence and sample length diagnostics, and evaluation of the performance of a model using drop-k validation or against simulated data. Template model specifications can be generated using a standard lme4-style formula interface to assist users less familiar with the BUGS syntax. ...

...HeatmapGenerator can also be used to make heatmaps in a variety of other non-medical fields. HeatmapGenerator is peer-reviewed published software (http://www.scfbm.org/content/9/1/30). Please cite: [Khomtchouk et al.: "HeatmapGenerator: High performance RNAseq and microarray visualization software suite to examine differential gene expression levels using an R and C++ hybrid computational pipeline." Source Code for Biology and Medicine, 2014 9:30] HeatmapGenerator source code is available at: https://github.com/Bohdan-Khomtchouk/HeatmapGenerator Bohdan Khomtchouk wishes to acknowledge the support of the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program. ...

...Perform evaluation on alignment quality reals that CUSHAW3 consistently outperforms CUSHAW2, BWA-MEM, Bowtie2 and GEM in terms of single-end and paired-end alignment. Furthermore, our aligner has demonstrated better paired-end alignment performance than Novalign3 for short-reads with high error rates.

High-throughput next generation sequencing (NGS) technology has quickly emerged as a powerful tool in many aspects of biomedical research. However, along with its rapid development, the data magnitude and analysis complexity for NGS far exceed the capacity and capability of traditional small-scale computing facilities, such as multithreading algorithms on standalone workstations.

PASHA is a parallel short read assembler for large genomes using de Bruijn graphs. Taking advantage of both shared-memory multi-core CPUs and distributed-memory compute clusters, PASHA has demonstrated its potential to perform high-quality de-novo assembly of large genomes in reasonable time with modest computing resources. Our evaluation using three small real paired-end datasets shows that PASHA is able to produce better assemblies with comparable genome coverage and mis-assembly rates compared to three leading assemblers: Velvet, ABySS and SOAPdenovo. Moreover, PASHA achieves the fastest speed for all three datasets on a single CPU. ...

parFE is fully-parallel high-performance finite element code targeted to the modeling of trabecular bones in humans. It employs scalable multigrid solvers for efficient solutions on massively parallel computers.