Search Results for "data analytics"

PINCIS.pl (PIcs N-/C-terminal Inferred Substrates perl script) is a small, command line tool to designate and analyze PICS (Schilling et al., Nat. Protocols, 2011) data to gain the prime and non-prime site specificity of proteases. Thus, the script filters given peptide lists for library peptides (generated by the digestion protease in the proteomics workflow rather then the protease of interest) and prints out lists of inferred N- and C-terminal cleavage window extensions which can be...

The OpenGEREA is a open enrichment analysis framework for gene expression regulation data analysis.

Processing of smallRNA-Seq data to gather biologically relevant information requires application of multiple statistical and bioinformatics tools from different sources, each focusing on a specific step of the analysis pipeline. The analytical workflow can be challenging for the continuous interventions by the operator, a critical factor when large numbers of datasets need to be analyzed at once. To allow a flexible and comprehensive analysis of smallRNA-Seq data we designed a novel modular...

The q utility is a platform for creating and managing data analysis pipelines. It expands the value of your existing job scheduler - either Grid Engine or TORQUE PBS - through numerous functions that help you organize, submit, monitor, manage and share your informatics work. Data processing pipelines require high-level organization and parallelization of work to optimize resource utilization and decrease the time to results. q (from queue) allows complex job sequences to be efficiently...

Detecting low-level mutations by utilizing the re-sequencing error profile of the data

The Canopy project is an initiative to merge and expand the functionality of Perl-speaks-NONMEM (PsN), Census, Xpose and PopED. The goal is to produce a coherent, inclusive and convenient platform for pharmacometric data analysis.

Open, extensible web-based collaborative platform for microarray gene expression, sequence and PPI data analysis, exposing distinct chainable components for clustering, pattern discovery, statistics (thru R), machine-learning algorithms and visualization