Chapter 4
GENETIC ALGORITHM
Overview
Genetic Algorithm is a sequential procedure developed from the science involved in genetic behaviour organisms for optimization purpose. Working Principle of GA includes the simulation of evolution theory in which, the initial set of “population” is selected in random, and then successive "generations" of solutions are reproduced till the optimal convergence. Existence of the fittest individual and natural selection operators is the main agenda of GA process. Philosophically one can say that GAs are based on Darwin’ theory of survival of the fittest. Genetic algorithm is a method for solving optimization problems that is based on natural selection, the process that drives biological evolution. Being analogous to genetics, it is a long complex thread of DNAs and RNAs containing the hereditary data, by which a traits of each individual can be determined, as chromosomes. Each trait in living organisms is being coded with some combination of DNAs like A (Adenine), C (Cytosine), T (Thymine) and G (Guanine).
During reproduction, changes in the chromosome is expected naturally due to the process called “crossover” in which chromosomes from the parent gets exchanged randomly. The chromosomes developed in offspring will definitely shows some traits of both the parents. In most rare cases the chromosomes gets replicated resulting in an offspring with no resemblance to parents. Now to make it clear, regarding the “mutation” process let us go further genetics; consider a case in which a parent chromosome having A-C-G-C-T produces an offspring of A-C-T-C-T due to some natural mistakes. Look onto a similar case when a typist is copying a book and make mistakes by copying wrongly spelled words which has no...
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...or by combining the vector entries of a pair of parents -- crossover.
Replaces the current population with the children to form the next generation.
The algorithm stops when one of the stopping criteria is met.
Fig. 4.6 Flow Chart of working principle of Genetic algorithm
The genetic algorithm is unique from other standard optimization as given:
Table 4.1 Standard Algorithm versus Genetic Algorithm.
Standard Algorithm Genetic Algorithm
Generates only a single point solution for each iteration, a sequence of those converging to the optimal solution. Generates a population of points for each iteration, leading to multiple options for solution out of which the best is to be selected.
Selects the succeeding point of the sequence by a deterministic computation approach. Selects the succeeding population by computations that involve random choices.
Due to the randomness of mutations, poor traits can come back into the gene pool after a number of generations.
. Other mistakes that can occur during meiosis include translocation, within which a part of one chromosome becomes connected to another, and deletion, in which part of one chromosome is lost entirely. The severity of the results of those disorders depends entirely on the dimensions of the chromosome fragment concerned and, therefore, the genetic data contained in it. Modern technology will find these genetic abnormalities early within the development of the foetus, however at the moment, very little will be done to correct or perhaps treat the diseases ensuing from
Mutation happens when the DNA gene gets changed, moves, or is damaged. When this happens it causes the genetic message to be carried by that gene to be different. This process can occur in somatic cells. The somatic cells are all the cells that are a living organism except the reproductive cells, meaning the body. For example, the skin cells on your legs are and will not be passed on to ones offsprings. In addition those leg cells will not effect the evolution. Another occurrence is called gametic mutations, which is in a woman's eggs and or in a man's sperm. These are cells that are and can be passed on to ones offsprings, and they are the essentials for the evolution. There are three effects mutation causes to a species. Species can only takes on one of the three. The three effects are bad, neutral, and good. Having a bad mutation can cause one to have a harder time being able to survive. Having a neutral mutation will not change or help one to survive. Having a good mutation will help one to survive and have a better chance of survival. However, mutation is random in the evolution, and provides raw material for natural selection, genetic drift, and gene flow...
Genetic Engineering has recently become a contentious topic within medical and social circles. Controversial topics such as Sex Selection and Designer Babies are linked to Genetic engineering. They are destructive in every circumstance. Genetic Engineering is detrimental towards the individual and all posterity.
It was originally developed for the AdvanceMAME project in the year 2001 to improve the
I do believe that there is a meaningful distinction between population and individual- level eugenics. I believe that the main difference between the two comes down to choice. When thinking about population-level eugenics, it is hard to imagine scenario that does not involve the government’s will being enforced on the population. A governing body would essentially be implementing artificial natural selection by selecting the phenotypes in the population that they deem the most favorable.
Mutation results in the changes in physical or physiology of an organism. Like in the movie, Mystique who can change someone else physically. Mutation could be beneficial, neutral or harm the organisms as mutation occur randomly. In the movie, the mutation that occur in their X genes led to super ability which is beneficial. However, mutation in the movie is not possible in real life. This is because mutation in human in chromosomal mutation only harm and will not give any superpower like in the movie. Chromosomal mutation in human are as a result of deletion, duplication, inversion and translocation of chromosomes. All these will results in either excess chromosomal numbers or less chromosomal numbers, Aneuploidy such as Down syndrome. Mutation is one of the reasons which is one of the factor that led to
Cormen T. H, Leiserson C. E., Rivest R. L. and Stein C. [1990] (2001). “Introduction to Algorithms”, 2nd edition, MIT Press and McGraw-Hill, ISBN 0-262-03293-7, pp. 27–37. Section 2.3: Designing algorithms..
A genetic mutation is a permanent change in the sequence of the DNA that makes up a gene. A mutation of these sorts can be caused by either inheritance from the parent or caused sometime during the life of someone. The mutation that has been inherited is called a germline mutation. Germline mutations affect virtually the entire body, and they seem to be present in every cell. A somatic mutation, or one that is caused in the DNA of a single cell sometime during the life, can be caused by an environmental factor or a wrong bonding in the DNA molecule. These cannot be passed down to the next generation of children because they occur in a specific cell as opposed to in a reproductive cell. Some mutations occur in the embryo as it is growing. These may occur during cell division, and some of the cells may or may not inherit this mutation. Some mutations are extremely rare, and others are incredibly common. Those that occur in more than one percent across a population are considered polymorphisms. Polymorphisms are considered normal variations in DNA, and they are known to cause simple changes such as variations in blood types and hair color. Although these are not typically fatal, they can influence the creation of some disorders (Lister Hill National Center for Biomedical Communications, U.S. National Library of Medicine, National Institutes of Health, Department of Health and Human Services, USA.gov, 2013).
Inside the cells that produce sperm and eggs, chromosomes become paired. While they are pressed together, the chromosomes may break, and each may swap a portion of its genetic material for the matching portion from its mate. This form of recombination is called crossing-over. When the chromosomes glue themselves back together and separate, each has picked up new genetic material from the other. The constellation of physical characteristics it determines is now different than before crossing-over.
Due to the development of ICT, adaptive learning, which takes into account individual learners’ needs, is changing. Learners’ learning styles are one of the most significant characteristics. They can be categorized according to a number of criteria which are based on cognitive and emotional components of personality. Their combination leads to the countless individual variants of real learning methods which – to a certain degree – can be influenced by the current e-learning resources. When the e-learning resources can react to the learners’ input characteristics or their learning results, they become adaptive e-learning systems (AES) or intelligent AES.
Synthetic biology, also known as synbio, is a new form of research that began in the year 2000. The Action Group on Erosion, Technology and Concentration (ETC Group) says that synthetic biology is bringing together “engineering and the life sciences in order to design and construct new biological parts, devices and systems that do not currently exist in the natural world’ (Synthetic Biology). Synthetic biology is aiming to create safer medicines, clean energy, and help the environment through synthetically engineered medicines, biofuels, and food. Because synthetic biology has only existed for fourteen years, there is controversy involving its engineering ethics. In this literature review, I am going to summarize and correlate the International Association for Synthetic Biology (IASB) Code of Conduct for Gene Synthesis, the impact of synthetic biology on people and the environment, and the philosophical debates.
Genetic algorithms are a randomized search method which "breeds" effective solutions to problems through simulation of Darwinian Evolution. Large numbers of potential solutions are created at random. The solutions which show the most promise are then breed together to produce new solutions which receive most of their 'genetic stock' from the better solutions in the previous generation. This is similar to the "survival of the fittest" shown in biological systems, where the individuals which are best adapted to their environment breed more offspring, resulting in the better adapted genetic material carrying forward into future generations.
Genetic modification is currently at the forefront of modern science and is being utilised in various fields such as medicine, agriculture and industry. Genetically Modified or transgenic organisms are organisms that have been genetically altered in a specific way for a particular purpose. It is now possible for scientists to exchange genes from one species of organism to another. This process is performed when certain characteristics of one organism are desired in another organism of a different species. For example a pig could be genetically engineered so that it will produce human insulin for those suffering from diabetes. Also, it is seen that it could be possible to cure certain allergies or diseases by replacing the genes responsible for causing the allergy or disease in one organism with that of a gene belonging to an organism that has a resistance to the specific allergen.
Genetic engineering seems decades away, but through modern technology, it has recently entered the human realm. Some believe genetic engineering will bring forth great advancements in the human brain and body, but instead some believe one mistake creates a world where every child will be genetically engineered just to keep up with the rest of society. Many times, the media plays a very strong role in the image of this issue, and masks the true identity of this social injustice. However, what forms of genetic engineering can be done in humans today? What is in store for the future? What are the risks and what could be the possible benefits? Currently gene therapy is one of the only ways to change the genetic makeup of an animal or human. Also,