In data mining, cluster analysis is used to classify a set of observations into two or more mutually exclusive unknown groups, based on combinations of the interval variables. The purpose is to discover a system of organizing observations, usually genes, and proteins into groups, where members of the groups share properties in common. In Creative Proteomics, we can interpret the data you collected with a set of typical clustering methodologies, algorithms, and applications, which include partitioning methods such as k-means, hierarchical methods and density-based methods. Your data can be interpreted and visualized with our assistance.
Clustering analysis generally consists of the following steps:
Applications in the field of computational biology for clustering analysis:
Clustering analysis services provided by Creative Proteomics include:
How to place an order:
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As one of the leading omics industry company in the world! Creative Proteomics now is opening to provide clustering analysis service for our customers. With over 8 years experience in the field of bioinformatics, we are willing to provide our customer the most outstanding service! Contact us for all the detailed informations!