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BMCBI
2010
118views more  BMCBI 2010»
15 years 7 months ago
From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification
Background: Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limit...
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Pa...
BMCBI
2007
146views more  BMCBI 2007»
15 years 7 months ago
Bayesian hierarchical model for transcriptional module discovery by jointly modeling gene expression and ChIP-chip data
Background: Transcriptional modules (TM) consist of groups of co-regulated genes and transcription factors (TF) regulating their expression. Two high-throughput (HT) experimental ...
Xiangdong Liu, Walter J. Jessen, Siva Sivaganesan,...
DKE
2008
79views more  DKE 2008»
15 years 7 months ago
Extracting k most important groups from data efficiently
We study an important data analysis operator, which extracts the k most important groups from data (i.e., the k groups with the highest aggregate values). In a data warehousing co...
Man Lung Yiu, Nikos Mamoulis, Vagelis Hristidis
RECOMB
2002
Springer
16 years 7 months ago
A new approach to analyzing gene expression time series data
We present algorithms for time-series gene expression analysis that permit the principled estimation of unobserved timepoints, clustering, and dataset alignment. Each expression p...
Ziv Bar-Joseph, Georg Gerber, David K. Gifford, To...
ICDE
2010
IEEE
273views Database» more  ICDE 2010»
16 years 6 months ago
WikiAnalytics: Ad-hoc Querying of Highly Heterogeneous Structured Data
Searching and extracting meaningful information out of highly heterogeneous datasets is a hot topic that received a lot of attention. However, the existing solutions are based on e...
Andrey Balmin, Emiran Curtmola