SynthEx is a comprehensive suite of tools for CNA detection and tumor heterogeneity profiling. It is tailored to cater for the multiple characteristics of different next generation sequencing technologies.
The metaBIT pipeline proposes tools for visualising microbial profiles (barplots, heatmaps) and performing a range of statistical analyses (diversity indices, hierarchical clustering and principal coordinate analysis). It uses as input fastq files containing trimmed reads from shotgun high through-put sequencing.
X2K (Expression2Kinases) is a method to identify upstream regulators likely responsible for observed patterns in genome-wide gene expression. By integrating ChIP-seq/chip and position-weight-matrices (PWMs) data, protein-protein interactions, and kinase-substrate phosphorylation reactions, X2K can better identify regulatory mechanisms upstream of genome-wide differences in gene expression. X2K first infers the most likely transcription factors that regulate the differences in gene expression, then use protein-protein interactions to connect the identified transcription factors using additional proteins for building transcriptional regulatory subnetworks centered on these factors, and finally use kinase-substrate protein phosphorylation reactions, to identify and rank candidate protein-kinases that most likely regulate the formation of the identified transcriptional complexes.
NOVA is a program designed to analysis complexome profiling data. A graphical user interface (GUI) provides various visualization tools, such as heat maps and 2D plots. nova gui Several hierarchical clustering algorithms (e.g., single linkage, average linkage, Wards linkage), different distance measures (e.g., Euclidean distance, Manhattan distance, Pearson distance), and various normalization techniques are implemented. Many additional functions like zooming, searching for proteins, image export, and automatic file format recognition support intuitive handling for biologists.
The mOTUs profiler is a computational tool that estimates relative abundance of known and currently unknown microbial community members using metagenomic shotgun sequencing data.
GEPIS (Gene Expression Profiling in silico), is a bioinformatics tool that integrates EST and tissue source information to compute gene expression patterns in a large panel of normal and tumor samples.
Yan Zhang, David A. Eberhard, Gretchen D. Frantz, Patrick Dowd, Thomas D. Wu, Yan Zhou, Colin Watanabe, Shiuh-Ming Luoh, Paul Polakis, Kenneth J. Hillan, William I. Wood and Zemin Zhang GEPIS-quantitative gene expression profiling in normal and cancer tissues
Bioinformatics, Oct. 12 2004, Vol. 20, No. 15, pp2390-2398