Background: This paper describes an automated method for finding clusters of interconnected proteins in protein interaction networks and retrieving protein annotations associated ...
Ruth Dunn, Frank Dudbridge, Christopher M. Sanders...
Numerous clustering algorithms, their taxonomies and evaluation studies are available in the literature. Despite the diversity of different clustering algorithms, solutions delive...
Anil K. Jain, Alexander P. Topchy, Martin H. C. La...
Data sets in astronomy are growing to enormous sizes. Modern astronomical surveys provide not only image data but also catalogues of millions of objects (stars, galaxies), each ob...
Bilkis J. Ferdosi, Hugo Buddelmeijer, Scott Trager...
—Normalization before clustering is often needed for proximity indices, such as Euclidian distance, which are sensitive to differences in the magnitude or scales of the attribute...
Abstract. Finding correlation clusters in the arbitrary subspaces of highdimensional data is an important and a challenging research problem. The current state-of-the-art correlati...