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BMCBI
2007
207views more  BMCBI 2007»
13 years 5 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...
BIOINFORMATICS
2006
92views more  BIOINFORMATICS 2006»
13 years 5 months ago
What should be expected from feature selection in small-sample settings
Motivation: High-throughput technologies for rapid measurement of vast numbers of biological variables offer the potential for highly discriminatory diagnosis and prognosis; howev...
Chao Sima, Edward R. Dougherty
ICONIP
2010
13 years 2 months ago
Exploring Features and Classifiers to Classify MicroRNA Expression Profiles of Human Cancer
Recently, some non-coding small RNAs, known as microRNAs (miRNA), have drawn a lot of attention to identify their role in gene regulation and various biological processes. The miRN...
Kyung-Joong Kim, Sung-Bae Cho
BMCBI
2007
175views more  BMCBI 2007»
13 years 5 months ago
Fast automated cell phenotype image classification
Background: The genomic revolution has led to rapid growth in sequencing of genes and proteins, and attention is now turning to the function of the encoded proteins. In this respe...
Nicholas A. Hamilton, Radosav S. Pantelic, Kelly H...
BMCBI
2010
113views more  BMCBI 2010»
13 years 5 months ago
Improving performance of mammalian microRNA target prediction
Background: MicroRNAs (miRNAs) are single-stranded non-coding RNAs known to regulate a wide range of cellular processes by silencing the gene expression at the protein and/or mRNA...
Hui Liu, Dong Yue, Yidong Chen, Shou-Jiang Gao, Yu...