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BMCBI
2006
186views more  BMCBI 2006»
13 years 4 months ago
Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method
Background: Quantitative simultaneous monitoring of the expression levels of thousands of genes under various experimental conditions is now possible using microarray experiments....
Xiaoli Li, Yin-Chet Tan, See-Kiong Ng
BMCBI
2008
111views more  BMCBI 2008»
13 years 4 months ago
Information-based methods for predicting gene function from systematic gene knock-downs
Background: The rapid annotation of genes on a genome-wide scale is now possible for several organisms using high-throughput RNA interference assays to knock down the expression o...
Matthew T. Weirauch, Christopher K. Wong, Alexandr...
BMCBI
2008
160views more  BMCBI 2008»
13 years 4 months ago
Predicting cancer involvement of genes from heterogeneous data
Background: Systematic approaches for identifying proteins involved in different types of cancer are needed. Experimental techniques such as microarrays are being used to characte...
Ramon Aragues, Chris Sander, Baldo Oliva
BIBM
2008
IEEE
108views Bioinformatics» more  BIBM 2008»
13 years 11 months ago
Systematic Evaluation of Scaling Methods for Gene Expression Data
Even after an experimentally prepared gene expression data set has been pre-processed to account for variations in the microarray technology, there may be inconsistencies between ...
Gaurav Pandey, Lakshmi Naarayanan Ramakrishnan, Mi...
BMCBI
2007
207views more  BMCBI 2007»
13 years 4 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...