Gene: The representation of a gene in a chromosome for genetic...

In galgo: Genetic Algorithms for Multivariate Statistical Models from Large-Scale Functional Genomics Data

Description

Represents the behaviour of a gene in a chromosome for the genetic algorithm. The default properties are supposed to be used in the variable selection problem for microarray data. However, they can be used for any other problem. In addition, any other wanted variable can be added.

See references for Genetic Algorithms.

Usage

Gene(id=0, shape1=0, shape2=0, generateFunc=runifInt, ...)

Arguments

id	To identify the object.
shape1	Parameter for a distribution. Used to generate a random value for a gene (mean, minimum, alfa, etc).
shape2	Parameter for a distribution. Used to generate a random value for a gene (sd, maximum, beta, etc).
generateFunc	Function that generate a random value for a gene using the above shape parameters. This function would be used to get an initial value and to mutate a gene. The default is a random uniform integer with shape1 as minimum and shape2 as maximum (either inclusive). The parameters used in the call are object, n, shape1, and shape2. The random value generated is not saved. If future values depends on the previous, you must save it explicitly in the object.
...	Other user named values to include in the object.

Class

Package: galgo
Class Gene

Object
~~|
~~+--Gene

Directly known subclasses:

public static class Gene
extends Object

Fields and Methods

Methods:

	as.double	Converts the gene parameters (shape1, shape2) to its numerical representation.
	as.matrix	Converts the gene parameters (shape1, shape2) to matrix.
	generateRandom	Generates a random value from the defined function.
	mutate	Mutates a gene.
	newCollection	Generates a list of cloned objects.
	newRandomCollection	Generates a list of cloned objects and random values.
	print	Prints the representation of a gene object.
	reInit	Erases all internal values in order to re-use the object.
	summary	Prints the representation of a gene object.

Methods inherited from Object:
as.list, unObject, $, $<-, [[, [[<-, as.character, attach, clone, detach, equals, extend, finalize, getFields, getInstanciationTime, getStaticInstance, hasField, hashCode, ll, load, objectSize, print, save

Author(s)

Victor Trevino. Francesco Falciani Group. University of Birmingham, U.K. http://www.bip.bham.ac.uk/bioinf

References

Goldberg, David E. 1989 Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Pub. Co. ISBN: 0201157675

See Also

Chromosome. Niche. World. Galgo. BigBang. runifInt.

Examples

  ge <- Gene(shape1=1, shape2=100)
  ge

galgo documentation built on May 2, 2019, 4:20 a.m.