Deep gene selection method to select genes from microarray datasets for cancer classification
نویسندگان
چکیده
منابع مشابه
A Robust Gene Selection Method for Microarray-based Cancer Classification
Gene selection is of vital importance in molecular classification of cancer using high-dimensional gene expression data. Because of the distinct characteristics inherent to specific cancerous gene expression profiles, developing flexible and robust feature selection methods is extremely crucial. We investigated the properties of one feature selection approach proposed in our previous work, whic...
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Gene Selection is one class of most used data analysis algorithms on microarray datasets. The goal of gene selection algorithms is to filter out a small set of informative genes that best explains experimental variations. Traditional gene selection algorithms are mostly single-gene based. Some discriminative scores are calculated and sorted for each gene. Top ranked genes are then selected as i...
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Background & objective: Microarray and next generation sequencing (NGS) data are the important sources to find helpful molecular patterns. Also, the great number of gene expression data increases the challenge of how to identify the biomarkers associated with cancer. The random forest (RF) is used to effectively analyze the problems of large-p and smal...
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ژورنال
عنوان ژورنال: BMC Bioinformatics
سال: 2019
ISSN: 1471-2105
DOI: 10.1186/s12859-019-3161-2