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BIBE
2004
IEEE
120views Bioinformatics» more  BIBE 2004»
13 years 8 months ago
Identifying Projected Clusters from Gene Expression Profiles
In microarray gene expression data, clusters may hide in subspaces. Traditional clustering algorithms that make use of similarity measurements in the full input space may fail to ...
Kevin Y. Yip, David W. Cheung, Michael K. Ng, Kei-...
EDM
2010
152views Data Mining» more  EDM 2010»
13 years 6 months ago
Mining Students' Interaction Data from a System that Support Learning by Reflection
In this paper we utilising some popular educational data mining (EDM) methods to explore and mine educational data resulted from a system that supports reflection for learning call...
Rajibussalim
BMCBI
2008
131views more  BMCBI 2008»
13 years 4 months ago
Modifying the DPClus algorithm for identifying protein complexes based on new topological structures
Background: Identification of protein complexes is crucial for understanding principles of cellular organization and functions. As the size of protein-protein interaction set incr...
Min Li, Jianer Chen, Jianxin Wang, Bin Hu, Gang Ch...
BMCBI
2010
214views more  BMCBI 2010»
13 years 4 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
PERVASIVE
2011
Springer
12 years 7 months ago
Identifying Important Places in People's Lives from Cellular Network Data
People spend most of their time at a few key locations, such as home and work. Being able to identify how the movements of people cluster around these “important places” is cru...
Sibren Isaacman, Richard Becker, Ramón C&aa...