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» A Practical Algorithm to Find the Best Subsequence Patterns
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KDD
2004
ACM
211views Data Mining» more  KDD 2004»
14 years 7 months ago
Towards parameter-free data mining
Most data mining algorithms require the setting of many input parameters. Two main dangers of working with parameter-laden algorithms are the following. First, incorrect settings ...
Eamonn J. Keogh, Stefano Lonardi, Chotirat (Ann) R...
HCI
2009
13 years 5 months ago
Mind-Mirror: EEG-Guided Image Evolution
Abstract. We propose a brain-computer interface (BCI) system for evolving images in realtime based on subject feedback derived from electroencephalography (EEG). The goal of this s...
Nima Bigdely Shamlo, Scott Makeig
NIPS
2003
13 years 8 months ago
ICA-based Clustering of Genes from Microarray Expression Data
We propose an unsupervised methodology using independent component analysis (ICA) to cluster genes from DNA microarray data. Based on an ICA mixture model of genomic expression pa...
Su-In Lee, Serafim Batzoglou
ALMOB
2006
155views more  ALMOB 2006»
13 years 7 months ago
Refining motifs by improving information content scores using neighborhood profile search
The main goal of the motif finding problem is to detect novel, over-represented unknown signals in a set of sequences (e.g. transcription factor binding sites in a genome). The mo...
Chandan K. Reddy, Yao-Chung Weng, Hsiao-Dong Chian...
BMCBI
2008
259views more  BMCBI 2008»
13 years 7 months ago
DISCLOSE : DISsection of CLusters Obtained by SEries of transcriptome data using functional annotations and putative transcripti
Background: A typical step in the analysis of gene expression data is the determination of clusters of genes that exhibit similar expression patterns. Researchers are confronted w...
Evert-Jan Blom, Sacha A. F. T. van Hijum, Klaas J....