CANCERTOOL
	
	CANCERTOOL is a webtool that integrates gene expression data from various publicly available cancer studies, so that researchers can access quickly 
	and easily to a summary of relevant information as well as perform a number of basic analysis and visualize and represent the results in an output 
	format suitable for publication in scientific journals
	
	Publication
	
	
ClusterLocator
	
	Cluster Locator determines the number, size and position of all the clusters formed by the genes on a list of interest and statistically analyze 
	the distribution of those genes along the reference genome and the percentage of gene clustering found
	
	Publication
	
	
VerSeDa
	
	VerSeDa (Vertebrate Secretome Database) has been developed to accelerate the prediction process for whole secretomes (the full set of secreted 
	proteins by a given organism). Researchers are offered a reliable repository where secretome information can be obtained.
	
	Publication
	
	
PECAS
	
	PECAS allows users to gain access to a well established analysis pipeline on prediction of secreted proteins. This tool enables potential users to carry 
	out predictions of secreted proteins in a single submission step (through the web interface) avoiding big data management issues. PECAS users can 
	perform classical secretome analysis (which is not currently offered in a pipeline format anywhere) on their sequences
	of interest by submitting their NGS data in a wide range of formats.
	
	Publication
	
	
seqCNA
	
	Deviations in the amount of genomic content that arise during tumorigenesis, called copy number alterations, are structural rearrangements that can critically
	affect gene expression patterns. We introduce seqCNA, a parallelized R package for an integral copy number analysis of high-throughput sequencing cancer data.
	
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SECRETOOL
	
	SECRETOOL is a webtool that comprises a group of tools that enable secretome predictions out of aminoacid sequence files, up to complete fungal proteomes, in one step.
	
	Publication
	
	
	CnaStruct
	
	CnaStruct is a bivariate segmentation method designed for allele-specific copy number analysis on SNP arrays. It is based on the structural change model (SCM) segmentation and is 
	designed to correctly detect all changes in mean, whether they occur in a single variable (LRR or BAF) or both variables.
	Publication
	
	CnaGen
	
	Generation of synthetic SNP-array tumour samples with extensive parameterization. Normal cell contamination, intra-tumour heterogeneity, genomic waves, baseline shift and other known factors are parameterizable.
	
	Publication
	
	miRanalyzer
	
	miRanalyser is a free web tool for the processing of small-RNAs data obtained using next generation sequencing techniques. 
	The input data consist of grouped sequence reads (sequence tags, unique reads), typically 16 to 26 bp long, and their expression values 
	(number of times the unique read has been found to be expressed in the experiment). 
	Publication