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» Identification of MCMC Samples for Clustering
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BMCBI
2007
207views more  BMCBI 2007»
13 years 7 months ago
Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clus
Background: The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell...
Nikhil R. Pal, Kripamoy Aguan, Animesh Sharma, Shu...
BMCBI
2002
136views more  BMCBI 2002»
13 years 7 months ago
Making sense of EST sequences by CLOBBing them
Background: Expressed sequence tags (ESTs) are single pass reads from randomly selected cDNA clones. They provide a highly cost-effective method to access and identify expressed g...
John Parkinson, David B. Guiliano, Mark L. Blaxter
CORR
2004
Springer
196views Education» more  CORR 2004»
13 years 7 months ago
Swarming around Shellfish Larvae
: The collection of wild larvae seed as a source of raw material is a major sub industry of shellfish aquaculture. To predict when, where and in what quantities wild seed will be a...
Vitorino Ramos, Jonathan Campbell, John Slater, Jo...
BMCBI
2010
151views more  BMCBI 2010»
13 years 7 months ago
Data reduction for spectral clustering to analyze high throughput flow cytometry data
Background: Recent biological discoveries have shown that clustering large datasets is essential for better understanding biology in many areas. Spectral clustering in particular ...
Habil Zare, Parisa Shooshtari, Arvind Gupta, Ryan ...
ICMLA
2007
13 years 8 months ago
SVMotif: A Machine Learning Motif Algorithm
We describe SVMotif, a support vector machine-based learning algorithm for identification of cellular DNA transcription factor (TF) motifs extrapolated from known TF-gene interact...
Mark A. Kon, Yue Fan, Dustin T. Holloway, Charles ...