Description Usage Arguments Value Author(s) References Examples

Interpolation of encoded protein sequences to a specific length. Interpol can be used to transform protein sequences to uniform length for subsequent classification.

1 |

`data` |
list of encoded protein sequences (as numerical vectors) |

`dims` |
interpolation value (desired dimensionality) |

`method` |
"linear": linear interpolation "spline": cubic spline interpolation "natural": fulfills natural boundary conditions "periodic": fulfills periodic boundary conditions "fmm": interpolation of Forsythe "average": interval based averaging |

returns the interpolated encoded amino acid sequences with desired dimensionality.

Dominik Heider, PhD, University of Duisburg-Essen, Germany

Heider D., Verheyen J., Hoffmann D.: Machine learning on normalized protein sequences, BMC Research Notes 2011, 4:94.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ```
#### V3 data
data(V3)
sequence = V3[1]
#### encoding of sequence a with descriptor 151 and with normalization [0,1]
b = AAdescriptor(sequence, 151, 2)
b
#### interpolation to length 27 with linear interpolation
c = Interpol(b, 27, "linear")
c
#### plotting
plot(unlist(b), type="l", col="darkgreen", ylim=c(-3,3), ylab="descriptor value", xlab="sequence position", lwd=2)
lines(seq(1,length(unlist(b)),(length(unlist(b))/length(as.vector(c)))),as.vector(c), col="red", lwd=2)
axis(3, at=seq(1,35, 35/27), labels=1:27)
``` |

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