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» A clustering method that uses lossy aggregation of data
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BMCBI
2007
156views more  BMCBI 2007»
13 years 9 months ago
Large-scale clustering of CAGE tag expression data
Background: Recent analyses have suggested that many genes possess multiple transcription start sites (TSSs) that are differentially utilized in different tissues and cell lines. ...
Kazuro Shimokawa, Yuko Okamura-Oho, Takio Kurita, ...
BMCBI
2008
146views more  BMCBI 2008»
13 years 9 months ago
A phase synchronization clustering algorithm for identifying interesting groups of genes from cell cycle expression data
Background: The previous studies of genome-wide expression patterns show that a certain percentage of genes are cell cycle regulated. The expression data has been analyzed in a nu...
Chang Sik Kim, Cheol Soo Bae, Hong Joon Tcha
IDA
2007
Springer
13 years 9 months ago
An unsupervised clustering approach for leukaemia classification based on DNA micro-arrays data
: DNA micro-arrays provide thousands of genomic expressions on the same subject. A main issue is then to find the subset of genes whose degeneration is responsible of a certain typ...
Simone Garatti, Sergio Bittanti, Diego Liberati, A...
ICASSP
2011
IEEE
13 years 25 days ago
Joint modeling of observed inter-arrival times and waveform data with multiple hidden states for neural spike-sorting
We present a novel, maximum likelihood framework for automatic spike-sorting based on a joint statistical model of action potential waveform shape and inter-spike interval duratio...
Brett Matthews, Mark Clements
PAKDD
2009
ACM
123views Data Mining» more  PAKDD 2009»
14 years 1 months ago
Clustering with Lower Bound on Similarity
We propose a new method, called SimClus, for clustering with lower bound on similarity. Instead of accepting k the number of clusters to find, the alternative similarity-based app...
Mohammad Al Hasan, Saeed Salem, Benjarath Pupacdi,...