Interpretable Machine Learning Approach Reveals Developmental Gene Expression Biomarkers for Cancer Patient Outcomes at Early Stages.
Alisha KamatTing JinSo Yeon MinFlaminia TalosJonas S. AlmeidaDaifeng WangPublished in: BCB (2018)
Keyphrases
- early stage
- gene expression
- gene expression profiles
- machine learning
- microarray
- differential expression
- ovarian cancer
- patient outcomes
- gene selection
- gene expression data
- dna microarray
- colon cancer
- microarray data
- breast cancer
- medical data
- gene expression data analysis
- cancer classification
- cancer diagnosis
- biological processes
- gene expression patterns
- gene expression data sets
- gene expression analysis
- genomic data
- analysis of gene expression
- drug discovery
- clinical data
- survival prediction
- biological networks
- text mining
- information extraction
- data mining
- regulatory networks
- gene networks
- real time
- binding sites
- computational biology
- natural language processing
- feature selection
- clinical practice
- statistical methods
- high throughput
- tissue samples
- support vector machine