Semi-supervised clustering uses a small amount of supervised data to aid unsupervised learning. One typical approach specifies a limited number of must-link and cannotlink constra...
Recent research in automated learning has focused on algorithms that learn from a combination of tagged and untagged data. Such algorithms can be referred to as semi-supervised in...
Hypertext interfaces are considered appropriate for information exploration tasks. The prohibitively expensive link creation effort, however, prevents traditional hypertext interf...
Background: Many statistical algorithms combine microarray expression data and genome sequence data to identify transcription factor binding motifs in the low eukaryotic genomes. ...
High-resolution array comparative genomic hybridization (aCGH) provides exon-level mapping of DNA aberrations in cells or tissues. Such aberrations are central to carcinogenesis an...
Amir Ben-Dor, Doron Lipson, Anya Tsalenko, Mark Re...