Strengths and limitations of microarray-based phenotype prediction: lessons learned from the IMPROVER Diagnostic Signature Challenge.
Adi L. TarcaMario LauriaMichael UngerErhan BilalStéphanie BouéKushal Kumar DeyJulia HoengHeinz KoepplFlorian MartinPablo MeyerPreetam NandyRaquel NorelManuel C. PeitschJohn Jeremy RiceRoberto RomeroGustavo StolovitzkyMarja TalikkaYang XiangChristoph ZechnerImprover Dsc CollaboratorsPublished in: Bioinform. (2013)
Keyphrases
- lessons learned
- microarray
- gene expression
- high throughput
- gene expression data
- microarray data
- genome wide
- case study
- protein function prediction
- prediction accuracy
- protein interaction
- gene ontology
- high dimensionality
- gene selection
- differentially expressed genes
- gene expression analysis
- biological networks
- gene expression profiling
- experimental conditions
- gene expression profiles
- molecular biology
- microarray analysis
- cancer classification
- gene networks
- gene expression data sets
- yeast cell cycle
- microarray data analysis
- microarray images
- analysis of gene expression
- microarray datasets
- biological data
- biologically meaningful
- gene expression datasets
- dna microarray
- regulatory networks
- gene expression microarray data
- tissue samples
- machine learning
- transcription factors
- systems biology