Department of Bioinformatics, MIT ADT University, Pune, India
Review Article
Identification of Cancer Types from Gene Expressions using Learning Techniques
Author(s): Swati B Bhonde*, Sharmila K Wagh and Jayashree R Prasad
Around the globe, the tumor is the leading cause of death. Early detection and prediction of a cancer type are important for a patient's wellbeing. Functional genomic data has recently been used in the effective and early detection of cancer. According to previous research, the use of microarray data in cancer prediction has evidenced two main problems as high dimensionality and limited sample size. Several researchers have used numerous statistical and machine learning - based methods to classify cancer types but still, limitations are there which makes cancer classification a difficult job. Deep Learning (DL) and Convolutional Neural Network (CNN) have proven effective in analyzing a wide range of unstructured data including gene expression data. In the proposed method gene expression data of five types of cancer is collected from The Cancer Genome Atlas (TCGA). Prominent featur.. View More»
