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» Active Clustering of Biological Sequences
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BMCBI
2007
139views more  BMCBI 2007»
13 years 7 months ago
Improving model predictions for RNA interference activities that use support vector machine regression by combining and filterin
Background: RNA interference (RNAi) is a naturally occurring phenomenon that results in the suppression of a target RNA sequence utilizing a variety of possible methods and pathwa...
Andrew S. Peek
BMCBI
2010
214views more  BMCBI 2010»
13 years 7 months ago
AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number
Background: Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the under...
Aaron M. Newman, James B. Cooper
ICPR
2010
IEEE
14 years 1 months ago
The Detection of Concept Frames Using Clustering Multi-Instance Learning
Abstract—The classification of sequences requires the combination of information from different time points. In this paper the detection of facial expressions is considered. Exp...
David Tax, Michel Valstar
BMCBI
2005
142views more  BMCBI 2005»
13 years 7 months ago
CLU: A new algorithm for EST clustering
Background: The continuous flow of EST data remains one of the richest sources for discoveries in modern biology. The first step in EST data mining is usually associated with EST ...
Andrey A. Ptitsyn, Winston Hide
BMCBI
2007
104views more  BMCBI 2007»
13 years 7 months ago
Predicting active site residue annotations in the Pfam database
Background: Approximately 5% of Pfam families are enzymatic, but only a small fraction of the sequences within these families (<0.5%) have had the residues responsible for cata...
Jaina Mistry, Alex Bateman, Robert D. Finn