A Synthetic Kinome Microarray Data Generator

A Synthetic Kinome Microarray Data Generator

Cellular pathways involve the phosphorylation and dephosphorylation of proteins. Peptide microarrays called kinome arrays facilitate the measurement of the phosphorylation activity of hundreds of proteins in a single experiment. Analyzing the data from kinome microarrays is a multi-step process. Typically, various techniques are possible for a particular step, and it is necessary to compare and...

SimTensor: A synthetic tensor data generator

SimTensor is a multi-platform, open-source software for generating artificial tensor data (either with CP/PARAFAC or Tucker structure) for reproducible research on tensor factorization algorithms. SimTensor is a stand-alone application based on MATALB. It provides a wide range of facilities for generating tensor data with various configurations. It comes with a user-friendly graphical user inte...

cDNA Microarray Data Normalization

A Spatial Biosurveillance Synthetic Data Generator in R

Introduction Development of new methods for the rapid detection of emerging disease outbreaks is a research priority in the field of biosurveillance. Because real-world data are often proprietary in nature, scientists must utilize synthetic data generation methods to evaluate new detection methodologies. Colizza et. al. have shown that epidemic spread is dependent on the airline transportation ...

TOntoGen: A Synthetic Data Set Generator for Semantic Web Applications

The development of algorithms and applications for the Semantic Web requires high-quality ontologies for testing and validation. Our work on the SemDis [6] project centers on discovering complex relationships between entities. This requires the development of path discovery algorithms for RDF graphs, and we have found that it is often difficult to find sufficient data sets for testing these alg...