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What is Mutation

Chapter 47
Handbook of Research on ICTs and Management Systems for Improving Efficiency in Healthcare and Social Care
Disease causing variant in the human genome.
Published in Chapter:
ICT Aspects of Next-Generation-Sequencing Applied to Molecular Diagnostics
Saskia Biskup (Institute for Clinical Genetics at Klinikum Stuttgart, Germany & CeGaT GmbH, Germany)
Copyright: © 2013 |Pages: 10
DOI: 10.4018/978-1-4666-3990-4.ch047
Abstract
Next-Generation-Sequencing (NGS) techniques are currently on the rise. This is seen as a revolution by (most) geneticists. The wealth of data stemming from Next-Generation-Sequencing will without a doubt lead to significant advances in the field of molecular diagnostics. On the clinical side, this will be higher detection rates of the genetic causes of particular diseases in patients. On the scientific side, NGS techniques will lead to the discovering of genes related to certain diseases (see, for example, Mardis, et al., 2009; Haack, et al., 2010; Lupski, et al., 2010). However, these advances come at a price: geneticists will be confronted with different and new ICT issues related to NGS. Because of the so far unknown amount of data stemming from NGS, these ICT issues need to be taken seriously. The purpose of this chapter is to give an overview on the different ICT aspects that come with the introduction of Next-Generation-Sequencing in molecular diagnostics.
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Chapter 47
ICT Aspects of Next-Generation-Sequencing Applied to Molecular Diagnostics
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Chapter 129
Machine Learning Techniques to Predict Software Defect
It takes one parent and replaces a randomly selected chunk of that parent with a randomly generated sequence of code.
Published in Chapter: Machine Learning Techniques to Predict Software Defect; From: Encyclopedia of Business Analytics and Optimization
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Chapter 112
Genetic Algorithms for Wireless Sensor Networks
The occasional (low probability) alteration of a bit position.
Published in Chapter: Genetic Algorithms for Wireless Sensor Networks; From: Encyclopedia of Artificial Intelligence
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Chapter 2
Genetic Processes Facilitating Pathogen Emergence
A change in the genetic code of an organism. Mutations can occur anywhere, but in sexually reproducing organisms, only those mutations that occur in the germ cells can be inherited by the progeny.
Published in Chapter: Genetic Processes Facilitating Pathogen Emergence; From: Tactical Sciences for Biosecurity in Animal and Plant Systems
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Chapter 41
Applications of JGA to Operations Management and Vehicle Routing
Genetic operator that alters one or more genes in a chromosome. Mutation is used to maintain genetic diversity in the population of individuals. It is analogous to biological mutation.
Published in Chapter: Applications of JGA to Operations Management and Vehicle Routing; From: Handbook of Research on Nature-Inspired Computing for Economics and Management
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Chapter 40
An Object-Oriented Framework for Rapid Genetic Algorithm Development
Genetic operator that alters one or more genes in a chromosome. Mutation is used to maintain genetic diversity in the population of individuals. It is analogous to biological mutation.
Published in Chapter: An Object-Oriented Framework for Rapid Genetic Algorithm Development; From: Handbook of Research on Nature-Inspired Computing for Economics and Management
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Chapter 97
Integration of Clinical and Genomic Data for Decision Support in Cancer
A change in the genetic material (usually DNA or RNA) of a living being. Mutations can happen for a lot of different reasons. They can happen because of errors during cell division, because of radiation, chemicals, and so forth.
Published in Chapter: Integration of Clinical and Genomic Data for Decision Support in Cancer; From: Encyclopedia of Healthcare Information Systems
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Chapter 16
Efficiency Analysis of Genetic Algorithm and Genetic Programming in Data Mining and Image Processing
Genetic operator for maintaining genetic diversity of population, i.e. changes on genes from one generation to another.
Published in Chapter: Efficiency Analysis of Genetic Algorithm and Genetic Programming in Data Mining and Image Processing; From: Handbook of Research on Manufacturing Process Modeling and Optimization Strategies
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Chapter 112
A Hybridized GA-Based Feature Selection for Text Sentiment Analysis
Mutations convert one or more genes from a chromosome from its original state. In the resolution of the solution, the solution may change completely from the previous solution.
Published in Chapter: A Hybridized GA-Based Feature Selection for Text Sentiment Analysis; From: Encyclopedia of Data Science and Machine Learning
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Chapter 4
Evolutionary Algorithms
Function that can possibly alter the genotype of an individual. Mutation is usually seen as an exploration operator, allowing the escape from local optima. A good mutation function should be ergodic.
Published in Chapter: Evolutionary Algorithms; From: Handbook of Research on Nature-Inspired Computing for Economics and Management
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Chapter 8
Evolutionary Computing to Examine Variation in Proteins with Evolution
Mutation might occur due to an abrupt but stable permanent alteration at the genetic or chromosome level, Mutations result from deformities nucleic acids; DNA that is unrepaired or to RNA. It is caused mainly due to radiation or due to the effect of the chemical mutagens. Mutations often tend to or may not tend to lead to certain discernible transitions in the phenotypic features that are observable in an organism. Mutations hold a chief role in the biological phenomena like; cancer, evolution, and the growth of immunity, as well as diversity at the junctions.
Published in Chapter: Evolutionary Computing to Examine Variation in Proteins with Evolution; From: Handbook of Research on Natural Computing for Optimization Problems
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Chapter 6
Genetic-Algorithm-Based Optimization of Clustering in Mobile Ad Hoc Network
Mutation is a stage in genetic algorithm in which one or more genes in a chromosome are modified to maintain diversity in the population of successive generations.
Published in Chapter: Genetic-Algorithm-Based Optimization of Clustering in Mobile Ad Hoc Network; From: Handbook of Research on Natural Computing for Optimization Problems
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Chapter 36
Modeling of Porphyrin Metabolism with PyBioS
Changes to the nucleotide sequence of the genetic material of an organism. Mutations can be caused by copying errors in the genetic material during cell division, by exposure to ultraviolet or ionizing radiation, chemical mutagens, or viruses.
Published in Chapter: Modeling of Porphyrin Metabolism with PyBioS; From: Handbook of Research on Systems Biology Applications in Medicine
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Chapter 90
Evolutionary Computing Approach for Ad-Hoc Networks
Genetic operation which randomly alters a chromosome to produce a new chromosome adding new solution to the solution-set.
Published in Chapter: Evolutionary Computing Approach for Ad-Hoc Networks; From: Encyclopedia of Artificial Intelligence
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Chapter 13
Evolution of Genetic Algorithms in Classification Rule Mining
It is process of GA, which changes two or more gene values in a chromosome from its initial state to add diversity in the population.
Published in Chapter: Evolution of Genetic Algorithms in Classification Rule Mining; From: Handbook of Research on Computational Intelligence for Engineering, Science, and Business
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Chapter 98
Finding Multiple Solutions with GA in Multimodal Problems
The other genetic operation included in evolutionary techniques to perform the reproduction stage. Mutation operator introduces new information in the system by random changes applied within the genetic individuals.
Published in Chapter: Finding Multiple Solutions with GA in Multimodal Problems; From: Encyclopedia of Artificial Intelligence
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Chapter 7
Genes: Structure, Replication, and Organization
An alteration in the DNA sequence due to an insertion, deletion or rearrangement of a single base pair or fragments.
Published in Chapter: Genes: Structure, Replication, and Organization; From: Examining the Causal Relationship Between Genes, Epigenetics, and Human Health
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