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» Analysis techniques for microarray time-series data
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SIGMETRICS
2003
ACM
115views Hardware» more  SIGMETRICS 2003»
14 years 1 months ago
Dynamic resource allocation for shared data centers using online measurements
Since web workloads are known to vary dynamically with time, in this paper, we argue that dynamic resource allocation techniques are necessary to provide guarantees to web applicat...
Abhishek Chandra, Weibo Gong, Prashant J. Shenoy
CSB
2005
IEEE
165views Bioinformatics» more  CSB 2005»
13 years 10 months ago
Sequential Diagonal Linear Discriminant Analysis (SeqDLDA) for Microarray Classification and Gene Identification
In microarray classification we are faced with a very large number of features and very few training samples. This is a challenge for classical Linear Discriminant Analysis (LDA),...
Roger Pique-Regi, Antonio Ortega, Shahab Asgharzad...
BMCBI
2006
131views more  BMCBI 2006»
13 years 8 months ago
The statistics of identifying differentially expressed genes in Expresso and TM4: a comparison
Background: Analysis of DNA microarray data takes as input spot intensity measurements from scanner software and returns differential expression of genes between two conditions, t...
Allan A. Sioson, Shrinivasrao P. Mane, Pinghua Li,...
WCE
2007
13 years 9 months ago
Gene Selection for Tumor Classification Using Microarray Gene Expression Data
– In this paper we perform a t-test for significant gene expression analysis in different dimensions based on molecular profiles from microarray data, and compare several computa...
Krishna Yendrapalli, Ram B. Basnet, Srinivas Mukka...
FUIN
2011
358views Cryptology» more  FUIN 2011»
13 years 3 days ago
Unsupervised and Supervised Learning Approaches Together for Microarray Analysis
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as ...
Indrajit Saha, Ujjwal Maulik, Sanghamitra Bandyopa...