Towards a potential pan-cancer prognostic signature for gene expression based on probesets and ensemble machine learning.
Davide ChiccoAbbas AlameerSara RahmatiGiuseppe JurmanPublished in: BioData Min. (2022)
Keyphrases
- high throughput
- microarray
- gene expression
- gene selection
- survival prediction
- machine learning
- gene expression profiles
- gene expression data
- dna microarray
- microarray technology
- analysis of gene expression
- gene expression data sets
- microarray data
- colon cancer
- cancer classification
- cancer diagnosis
- gene expression data analysis
- biological data
- tissue samples
- genomic data
- gene expression datasets
- gene ontology
- feature selection
- biological processes
- cluster ensemble
- gene expression patterns
- high dimensionality
- biological networks
- gene regulation
- gene expression microarray data
- gene interactions
- differential expression
- differentially expressed genes
- ovarian cancer
- breast cancer
- regulatory networks
- statistical methods
- decision trees
- support vector machine
- ensemble methods
- binding sites
- lung cancer
- knowledge discovery
- functional genomics
- natural language processing
- machine learning methods
- information extraction
- microarray datasets
- data sets
- text mining
- co occurrence
- prostate cancer