promotergene {kernlab} | R Documentation

## E. coli promoter gene sequences (DNA)

### Description

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.

### Usage

    data(promotergene)

### Format

A data frame with 106 observations and 58 variables. The first variable `Class` is a factor with levels `+` for a promoter gene and `-` for a non-promoter gene. The remaining 57 variables `V2 to V58` are factors describing the sequence. The DNA bases are coded as follows: `a` adenine `c` cytosine `g` guanine `t` thymine

### Source

UCI Machine Learning data repository
ftp://ftp.ics.uci.edu/pub/machine-learning-databases/molecular-biology/promoter-gene-sequences

### References

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)

### Examples

    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

[Package kernlab version 0.9-25 Index]