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» Network constrained clustering for gene microarray data
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ALMOB
2007
111views more  ALMOB 2007»
14 years 10 months ago
Transcriptional regulatory network discovery via multiple method integration: application to e. coli K12
Motivation: Transcriptional regulatory network (TRN) discovery from one method (e.g. microarray analysis, gene ontology, phylogenic similarity) does not seem feasible due to lack ...
Jingjun Sun, Kagan Tuncay, Alaa Abi Haidar, Lisa E...
BMCBI
2007
207views more  BMCBI 2007»
14 years 10 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...
ALIFE
2008
14 years 9 months ago
Exploring the Operational Characteristics of Inference Algorithms for Transcriptional Networks by Means of Synthetic Data
The development of structure-learning algorithms for gene regulatory networks depends heavily on the availability of synthetic data sets that contain both the original network and ...
Koenraad Van Leemput, Tim Van den Bulcke, Thomas D...
RECOMB
2007
Springer
15 years 10 months ago
Learning Gene Regulatory Networks via Globally Regularized Risk Minimization
Learning the structure of a gene regulatory network from time-series gene expression data is a significant challenge. Most approaches proposed in the literature to date attempt to ...
Yuhong Guo, Dale Schuurmans
PR
2006
116views more  PR 2006»
14 years 9 months ago
Shared farthest neighbor approach to clustering of high dimensionality, low cardinality data
Clustering algorithms are routinely used in biomedical disciplines, and are a basic tool in bioinformatics. Depending on the task at hand, there are two most popular options, the ...
Stefano Rovetta, Francesco Masulli