Search Results for "command shell"

Detecting allelic biases from high-throughput sequencing data requires an approach that maximises sensitivity while minimizing false positives. Here we present Allelome.PRO, an automated userfriendly bioinformatics pipeline, which uses high-throughput sequencing data from reciprocal crosses of two genetically distinct mouse strains to detect allele-specific expression and chromatin modifications. Allelome.PRO extends approaches used in previous studies that exclusively...

BSpipe is a comprehensive pipeline from sequence quality control and mapping to functional analysis of differentially methylated regions: (1) sequencing quality assessment, (2) sequence cleaning, (3) sequence read mapping, (4) methylation quantification, (4) sample comparisons based on methylation profile, (5) identification of DMRs (differentially methylated regions), (6) annotation of DMRs, (7) functional analysis of differentially methylated genes, (8) generation of input files...

TEACUP automates many aspects of running TCP performance experiments in a specially-constructed physical testbed. TEACUP enables repeatable testing of different TCP algorithms over a range of emulated network path conditions, bottleneck rate limits and bottleneck queuing disciplines. TEACUP utilises a text-based configuration file to define experiments as combinations of parameters specifying desired network path and end host conditions. When multiple values are provided (e.g. for TCP...

ncPRO-seq is a tool for annotation and profiling of ncRNAs from smallRNA sequencing data. It aims to interrogate and perform detailed analysis on small RNAs derived from annotated non-coding regions in miRBase, piRBase, Rfam and repeatMasker, and regions defined by users. The ncPRO pipeline also has a module to identify regions significantly enriched with short reads that can not be classified as known ncRNA families. ############# Docker version : download and run Dockerfile (go in...

Conjunto de scripts e aplicativos para criação, manutenção e utilização de banco de dados da MegaSena extraído de arquivo público fornecido pelo website da Caixa Econômica Federal.

Tools to build molecular-docking activity prediction models by PLS regression with iterative training and pose-selection. Descriptors include (i) docking score(s), (ii) pharmacophore features, (iii) multi-feature descriptors learned by decision trees.