Promoters have a region where a protein (RNA polymerase) must make contact and the helical DNA sequence must have a valid conformation so that the two pieces of the contact region spatially align. The data contains DNA sequences of promoters and non-promoters.
A data frame with 106 observations and 58 variables.
The first variable
Class is a factor with levels
+ for a promoter gene
- for a non-promoter gene.
The remaining 57 variables
V2 to V58 are factors describing the sequence.
The DNA bases are coded as follows:
UCI Machine Learning data repository
Towell, G., Shavlik, J. and Noordewier, M.
Refinement of Approximate Domain Theories by Knowledge-Based Artificial Neural Networks.
In Proceedings of the Eighth National Conference on Artificial Intelligence (AAAI-90)
data(promotergene) ## Create classification model using Gaussian Processes prom <- gausspr(Class~.,data=promotergene,kernel="rbfdot", kpar=list(sigma=0.02),cross=4) prom ## Create model using Support Vector Machines promsv <- ksvm(Class~.,data=promotergene,kernel="laplacedot", kpar="automatic",C=60,cross=4) promsv
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