EAT-Rice: A predictive model for flanking gene expression of T-DNA insertion activation-tagged rice mutants by machine learning approaches.
Chi-Chou LiaoLiang-Jwu ChenShuen-Fang LoChi-Wei ChenYen-Wei ChuPublished in: PLoS Comput. Biol. (2019)
Keyphrases
- gene expression
- machine learning approaches
- predictive model
- binding sites
- microarray
- gene expression data
- machine learning methods
- biological processes
- microarray data
- dna binding
- gene expression profiles
- data mining methods
- machine learning algorithms
- gene expression patterns
- historical data
- prediction model
- dna sequences
- gene regulation
- regulatory networks
- probabilistic model
- machine learning
- classification rules
- artificial neural networks
- data sets
- databases
- transcription factors
- neural network
- genomic data
- information retrieval
- association rules
- high throughput