Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
CANCER CLASSIFICATION BASED ON MICROARRAY GENE EXPRESSION DATA USING DCT AND ANN
56
Zitationen
1
Autoren
2009
Jahr
Abstract
In this paper, a stomach cancer detection system based on Artificial Neural Network (ANN), and the Discrete Cosine Transform (DCT), is developed. The proposed system extracts classification features from stomach microarrays using the DCT. The features extracted from the DCT coefficients are then applied to an ANN for classification (tumor or non—tumor). The microarray images used in this study were obtained from the Stanford Medical Database (SMD). Simulation results showed that the proposed system produces a very high success rate.
Ähnliche Arbeiten
Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2−ΔΔCT Method
2001 · 179.656 Zit.
Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles
2005 · 55.912 Zit.
<tt>edgeR</tt> : a Bioconductor package for differential expression analysis of digital gene expression data
2009 · 44.029 Zit.
limma powers differential expression analyses for RNA-sequencing and microarray studies
2015 · 42.262 Zit.
clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters
2012 · 37.426 Zit.