Practical Outcomes of Applying Ensemble Machine Learning Classifiers to High-Throughput Screening (HTS) Data Analysis and Screening.
Kirk SimmonsJohn KinneyAaron OwensDaniel A. KleierKaren BlochDave ArgentarAlicia WalshGanesh VaidyanathanPublished in: J. Chem. Inf. Model. (2008)
Keyphrases
- high throughput
- machine learning
- data analysis
- biological data
- microarray
- genome wide
- feature selection
- decision trees
- systems biology
- ensemble learning
- machine learning algorithms
- data acquisition
- machine learning methods
- training data
- ensemble classifier
- data mining
- drug discovery
- protein protein interactions
- mass spectrometry data
- genomic data
- ensemble methods
- flow cytometry
- classifier ensemble
- multiple classifier systems
- image analysis
- training set
- proteomic data
- learning algorithm
- data warehouse
- knowledge discovery
- dna sequencing
- pattern classification
- life sciences
- pattern recognition
- feature ranking
- random forest
- gene expression
- data collection
- data processing
- support vector machine
- feature extraction
- analysis of gene expression