Data Analysis

SilicoCyte™ performs crucial and highly accurate statistical data analysis functions to suit the requirements of researchers. SilicoCyte's™ extremely powerful and simple to use data mining query builder interface helps biologists to create powerful complex queries.

The results generated using this feature can be visualized in various formats (graphs & textual reports). SilicoCyte also provides an option to dynamically select data for further analysis, grouping and accessing detailed data for a data point.

Data Analysis features of SilicoCyte™ are:

	Time series analysis
	Hierarchical Clustering
	Similarity Measure
	Euclidean
	Correlation
	Cosine Correlation
	Manhattan
	Tanimotto Coefficient
	Half Square Euclidean
	Linkage Rules
	UPGMA
	WPGMA
	Single Linkage
	Complete Linkage
	K-Mean Clustering
	Similarity Measure
	Euclidean
	Correlation
	Cosine Correlation
	Manhattan
	Tanimotto Coefficient
	Half Square Euclidean
	Cluster initialization method
	Evenly Spaced Profiles
	Randomly generated Profiles
	Randomly Selected Profiles
	Self-Organizing Map
	Neighborhood function
	Bubble function
	Gaussian function
	Learning function
	Replicate analysis within and across microarrays
	Dynamic selection of query data
	Query builder
	Gene groups for use in analysis
	Probe groups for use in analysis
	Microarray groups for use in analysis