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ICDM
2009
IEEE
181views Data Mining» more  ICDM 2009»
13 years 3 months ago
Efficient Discovery of Frequent Correlated Subgraph Pairs
The recent proliferation of graph data in a wide spectrum of applications has led to an increasing demand for advanced data analysis techniques. In view of this, many graph mining ...
Yiping Ke, James Cheng, Jeffrey Xu Yu
BMCBI
2006
124views more  BMCBI 2006»
13 years 5 months ago
Network-based de-noising improves prediction from microarray data
Background: Prediction of human cell response to anti-cancer drugs (compounds) from microarray data is a challenging problem, due to the noise properties of microarrays as well as...
Tsuyoshi Kato, Yukio Murata, Koh Miura, Kiyoshi As...
CIKM
2006
Springer
13 years 9 months ago
Finding highly correlated pairs efficiently with powerful pruning
We consider the problem of finding highly correlated pairs in a large data set. That is, given a threshold not too small, we wish to report all the pairs of items (or binary attri...
Jian Zhang, Joan Feigenbaum
ICONIP
2010
13 years 2 months ago
Exploring Features and Classifiers to Classify MicroRNA Expression Profiles of Human Cancer
Recently, some non-coding small RNAs, known as microRNAs (miRNA), have drawn a lot of attention to identify their role in gene regulation and various biological processes. The miRN...
Kyung-Joong Kim, Sung-Bae Cho
APBC
2003
128views Bioinformatics» more  APBC 2003»
13 years 6 months ago
Machine Learning in DNA Microarray Analysis for Cancer Classification
The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it e...
Sung-Bae Cho, Hong-Hee Won