Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
Background: After complete sequencing of a number of genomes the focus has now turned to proteomics. Advanced proteomics technologies such as two-hybrid assay, mass spectrometry e...
Md. Altaf-Ul-Amin, Yoko Shinbo, Kenji Mihara, Ken ...
DNA copy number variants (CNV) are gains and losses of segments of chromosomes, and comprise an important class of genetic variation. Recently, various microarray hybridization ba...
Background: Agglomerative hierarchical clustering (AHC) is a common unsupervised data analysis technique used in several biological applications. Standard AHC methods require that...
Background: Microscopists are familiar with many blemishes that fluorescence images can have due to dust and debris, glass flaws, uneven distribution of fluids or surface coatings...