An empirical study of supervised learning for biological sequence profiling and microarray expression data analysis.
Abu H. M. KamalXingquan ZhuAbhijit S. PandyaSam HsuYong ShiPublished in: IRI (2008)
Keyphrases
- microarray
- biological sequences
- biological data
- high throughput
- supervised learning
- molecular biology
- data analysis
- gene expression levels
- microarray data
- gene expression
- gene sets
- gene expression data
- differential expression
- genome wide
- unsupervised learning
- binding sites
- experimental conditions
- gene ontology
- gene selection
- machine learning
- systems biology
- high dimensionality
- gene networks
- training data
- learning algorithm
- gene expression profiling
- protein sequences
- sequence data
- data collection
- microarray data analysis
- protein protein interactions
- training set
- gene expression profiles
- data processing
- data warehouse
- gene expression analysis
- cancer classification
- microarray images
- dna sequences
- microarray datasets
- computational biology
- data sets
- cluster analysis
- semi supervised
- knowledge discovery
- data mining
- transcription factors
- high dimensional data
- feature selection
- neural network
- databases