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Genetic Algorithms1 COMP305. Part II. Genetic Algorithms.

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Presentation on theme: "Genetic Algorithms1 COMP305. Part II. Genetic Algorithms."— Presentation transcript:

1 Genetic Algorithms1 COMP305. Part II. Genetic Algorithms.

2 Genetic Algorithms2 Topic 1. Biological motivation for Genetic Algorithms.

3 Genetic Algorithms3 Darwinian theory of Evolution (macroscopic). Species adapt to the environment via natural selection. The selection favors those species for survival and further evolution that are best adapted to the environmental condition – “survival of the fittest”. Phenotype is the manner of response and physical embodiment of an individual. There occur small, apparently random and undirected variations between the phenotypes of parents and their offspring. These mutations prevail through selection, if they prove their worth in light of the current environment; otherwise they perish.

4 Genetic Algorithms4 Production of offspring is the basic driving force for selection. In a favorable environment population grows exponentially. This growth is generally limited by finite resources. When resources are no longer sufficient to support all individuals in a population, only the fittest, i.e. those most effectively exploiting the resources, survive and produce offspring. In a hostile environment organisms in a population are at a selective advantage to exploit resources most effectively. Darwinian theory of Evolution (macroscopic).

5 Genetic Algorithms5 NeoDarwinism - synthetic theory of Evolution (microscopic). All living organisms consist of cells. Each cell in an organism contains the same set of one or more chromosomes – Chromosomes are strings of DNA that serve as a blueprint for the organism.

6 Genetic Algorithms6 Figure 1 This figure is purely diagrammatic. The two ribbons symbolize the two phosphate-sugar chains, and the horizontal rods the pairs of bases holding the chains together. The vertical line marks the fibre axis. Nature 171, (1953) © Macmillan Publishers Ltd. Molecular structure of Nucleic Acids WATSON, J. D. & CRICK, F. H. C. Medical Research Council Unit for the Study of Molecular Structure of Biological Systems, Cavendish Laboratory, Cambridge.

7 Genetic Algorithms7 Born: London, England, July 25, 1920 Died: London, England, April 16, 1958 Pioneer Molecular Biologist responsible for much of the research and discovery work that led to the understanding of the structure of DNA It was in Randall's lab that she crossed paths with Maurice Wilkins. She and Wilkins led separate research groups and had separate projects, although both were concerned with DNA. When Randall gave Franklin responsibility for her DNA project, no one had worked on it for months. Wilkins was away at the time, and when he returned he misunderstood her role, behaving as though she were a technical assistant. Both scientists were actually peers. His mistake, acknowledged but never overcome, was not surprising given the climate for women at the university then. Only males were allowed in the university dining rooms, and after hours Franklin's colleagues went to men-only pubs. At one point, Wilkins showed Watson one of Franklin's crystallographic portraits of DNA. When he saw the picture, the solution became apparent to him, and the results went into an article in Nature almost immediately. Franklin's work did appear as a supporting article in the same issue of the journal. A debate about the amount of credit due to Franklin continues. What is clear is that she did have a meaningful role in learning the structure of DNA and that she was a scientist of the first rank.

8 Genetic Algorithms8 NeoDarwinism - synthetic theory of Evolution (microscopic). A chromosome can be conceptually divided into genes --- Gene is a functional block of DNA coding a particular protein.

9 Genetic Algorithms9 NeoDarwinism - synthetic theory of Evolution (microscopic). DNA code. DNA alphabet: A - adenine, G - guanine, T - thymine, C – cytosine. DNA molecule consists of two ribbons of phosphate-sugar chains, and the horizontal rods the pairs of nitrogenous bases holding the chains together There exist only four different nitrogenous bases in DNA: adenine, guanine, thymine, cytosine.

10 Genetic Algorithms10 NeoDarwinism - synthetic theory of Evolution (microscopic). DNA code. DNA alphabet: A - adenine, G - guanine, T - thymine, C - cytosine.  The two chains held together by hydrogen bonds formed between pairs of bases.  Pairing is highly specific. It is always that Adenine pairs with Thymine, A = T; and Guanine pairs with Cytosine, G = C.  The precise sequence of bases carries the genetic information.

11 Genetic Algorithms11 NeoDarwinism - synthetic theory of Evolution (microscopic). DNA code. DNA alphabet: A - adenine, G - guanine, T - thymine, C - cytosine.  The precise sequence of bases carries the genetic information. Gene is a functional block of DNA coding a particular protein. Problem: there are just 4 letters in the DNA alphabet to code 20 amino acids found in proteins

12 Genetic Algorithms12 NeoDarwinism - synthetic theory of Evolution (microscopic). DNA code. DNA alphabet: A - adenine, G - guanine, T - thymine, C - cytosine.  Gene is a functional block of DNA coding a particular protein. Problem: there are just 4 letters in the DNA alphabet to code 20 amino acids found in proteins Solution: 1. there can not be one to one, i.e. one DNA letter per one amino acid, match.

13 Genetic Algorithms13 NeoDarwinism - synthetic theory of Evolution (microscopic). DNA code. DNA alphabet: A - adenine, G - guanine, T - thymine, C - cytosine. Problem: 4 letters in the DNA alphabet to code 20 amino acids found in proteins Solution: 1. there can not be one to one match. 2. There can not be a two nucleic bases to one amino acid match either, as it gives just 4 2 =16 different pairs of nucleotides < 20.

14 Genetic Algorithms14 NeoDarwinism - synthetic theory of Evolution (microscopic). DNA code. DNA alphabet: A - adenine, G - guanine, T - thymine, C - cytosine. Problem: 4 letters in the DNA alphabet to code 20 amino acids found in proteins Solution: 3 nucleic bases in combination as a triplet are required to code for each amino acid, as this gives 4 3 = 64 possible combinations or codons => the genetic code is based on the triplet codons.

15 Genetic Algorithms15 NeoDarwinism - synthetic theory of Evolution (microscopic). DNA code. The genetic code.  The genetic code is universal, as the codons that code for amino acids are the same in bacteria, plants and animals. T T Problem: 4 letters in the DNA alphabet to code 20 amino acids found in proteins Solution: the genetic code is based on the triplet codons.

16 Genetic Algorithms16 NeoDarwinism - synthetic theory of Evolution (microscopic). DNA code. The genetic code.  The genetic code is universal, as the codons that code for amino acids are the same in bacteria, plants and animals. T T Problem: 4 letters in the DNA alphabet to code 20 amino acids found in proteins Solution: the genetic code is based on the triplet codons.

17 Genetic Algorithms17 DNA code. Crossing-over (Recombination). Organisms with unpaired sets of chromosomes are called haploid. Organisms, whose chromosomes are arranged in pairs are called diploid. Most sexually reproducing organisms are diploid. During sexual reproduction, crossing-over or recombination of genes in parental chromosomes occurs. In each parent cell, a pair of chromosomes first doubles, then the chromosomes exchange genes, and finally produce four gametes, single chromosomes, ready to couple with the other parent gametes to form a new diploid cell Formation of gametes (Meiosis).

18 Genetic Algorithms18 DNA code. Mutations. Mutation is a random change of “letter”, single nucleotide in a chromosome. T T T T The genetic code.  Mutations usually result from copying errors in parental chromosomes and then are reproduced in offspring.

19 Genetic Algorithms19 NeoDarwinism - synthetic theory of Evolution (microscopic). Gene is a functional block of DNA coding a particular protein, see “gene encodes a trait, e.g. eye colour”. Different possible settings for a trait, e.g. blue, brown, hazel eye colour, are called alleles. Each gene is located at a particular locus (position) on the chromosome.

20 Genetic Algorithms20 NeoDarwinism - synthetic theory of Evolution (microscopic). The complete collection of all genetic material, all chromosomes taken together, is called the organisms genome or genotype. Gene is a functional block of DNA coding a particular protein, see “gene encodes a trait, e.g. eye colour”.

21 Genetic Algorithms21 NeoDarwinism - synthetic theory of Evolution (microscopic). Genes are transfer units of heredity. Genes are occasionally changed by mutations. Phenotype expresses complex interaction within the genotype as well as its interaction with environment. Source: Howell, F. C. (1966) Early man (pp ). Time-Life International. Modern biochemistry and genetics explain microscopic mechanisms of heredity.

22 Genetic Algorithms22 NeoDarwinism - synthetic theory of Evolution (microscopic). Genes are transfer units of heredity, and genotype is the total genetic information of an individual. Selection acts on an individual, thus an individual is a selection unit. Population is the evolving unit. Population as a unit confines a common gene pool including genotypes of all individuals. Modern biochemistry and genetics explain microscopic mechanisms of heredity.

23 Genetic Algorithms23 Natural Evolution. What is the Fitness ? Individual fitness is measured indirectly as the individual growth rate in comparison to others. The fitness is the individual propensity to survive and reproduce in a particular environment. Thus, Natural Selection according to the individual fitness is NOT an active driving force, IS differential survival and reproduction within a population.

24 Genetic Algorithms24 Individual fitness is measured indirectly as the individual growth rate in comparison to others. The fitness is the individual propensity to survive and reproduce in a particular environment. Thus, Natural Selection according to the individual fitness is NOT an active driving force, IS differential survival and reproduction within a population. SO, what is the fitness? Can we 1. map a given genotype into the corresponding phenotype and 2. map the phenotype into the individual fitness to survive and reproduce ? Not, actually… But the idea is so beautiful... Natural Evolution. What is the Fitness ?


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