Intelligent Bioinformatics
The Application of Artificial Intelligence Techniques to Bioinformatics Problems
(Sprache: Englisch)
Bioinformatics is contributing to some of the most important advances in medicine and biology. At the forefront of this exciting new subject are techniques known as artificial intelligence which are inspired by the way in which nature solves the problems it faces.
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Bioinformatics is contributing to some of the most important advances in medicine and biology. At the forefront of this exciting new subject are techniques known as artificial intelligence which are inspired by the way in which nature solves the problems it faces.
Klappentext zu „Intelligent Bioinformatics “
Bioinformatics is contributing to some of the most important advances in medicine and biology. At the forefront of this exciting new subject are techniques known as artificial intelligence which are inspired by the way in which nature solves the problems it faces. This book provides a unique insight into the complex problems of bioinformatics and the innovative solutions which make up 'intelligent bioinformatics'.Intelligent Bioinformatics requires only rudimentary knowledge of biology, bioinformatics or computer science and is aimed at interested readers regardless of discipline. Three introductory chapters on biology, bioinformatics and the complexities of search and optimisation equip the reader with the necessary knowledge to proceed through the remaining eight chapters, each of which is dedicated to an intelligent technique in bioinformatics.
The book also contains many links to software and information available on the internet, in academic journals and beyond, making it an indispensable reference for the 'intelligent bioinformatician'.
Intelligent Bioinformatics will appeal to all postgraduate students and researchers in bioinformatics and genomics as well as to computer scientists interested in these disciplines, and all natural scientists with large data sets to analyse.
Bioinformatics is contributing to some of the most important advances in medicine and biology. At the forefront of this exciting new subject are techniques known as artificial intelligence which are inspired by the way in which nature solves the problems it faces. This book provides a unique insight into the complex problems of bioinformatics and the innovative solutions which make up 'intelligent bioinformatics'.
Intelligent Bioinformatics requires only rudimentary knowledge of biology, bioinformatics or computer science and is aimed at interested readers regardless of discipline. Three introductory chapters on biology, bioinformatics and the complexities of search and optimisation equip the reader with the necessary knowledge to proceed through the remaining eight chapters, each of which is dedicated to an intelligent technique in bioinformatics.
The book also contains many links to software and information available on the internet, in academic journals and beyond, making it an indispensable reference for the 'intelligent bioinformatician'.
Intelligent Bioinformatics will appeal to all postgraduate students and researchers in bioinformatics and genomics as well as to computer scientists interested in these disciplines, and all natural scientists with large data sets to analyse.
Intelligent Bioinformatics requires only rudimentary knowledge of biology, bioinformatics or computer science and is aimed at interested readers regardless of discipline. Three introductory chapters on biology, bioinformatics and the complexities of search and optimisation equip the reader with the necessary knowledge to proceed through the remaining eight chapters, each of which is dedicated to an intelligent technique in bioinformatics.
The book also contains many links to software and information available on the internet, in academic journals and beyond, making it an indispensable reference for the 'intelligent bioinformatician'.
Intelligent Bioinformatics will appeal to all postgraduate students and researchers in bioinformatics and genomics as well as to computer scientists interested in these disciplines, and all natural scientists with large data sets to analyse.
Inhaltsverzeichnis zu „Intelligent Bioinformatics “
PrefacePart 1 Introduction
1 Introduction to the Basics of Molecular Biology
1.1 Basic cell architecture
1.2 The structure, content and scale of deoxyribonucleic acid (DNA)
1.3 History of the human genome
1.4 Genes and proteins
1.5 Current knowledge and the 'central dogma'
1.6 Why proteins are important
1.7 Gene and cell regulation
1.8 When cell regulation goes wrong
1.9 So, what is bioinformatics?
1.10 Summary of chapter
1.11 Further reading
2 Introduction to Problems and Challenges in Bioinformatics
2.1 Introduction
2.2 Genome
2.3 Transcriptome
2.4 Proteome
2.5 Interference technology, viruses and the immune system
2.6 Summary of chapter
2.7 Further reading
3 Introduction to Artificial Intelligence and Computer Science
3.1 Introduction to search
3.2 Search algorithms
3.3 Heuristic search methods
3.4 Optimal search strategies
3.5 Problems with search techniques
3.6 Complexity of search
3.7 Use of graphs in bioinformatics
3.8 Grammars, languages and automata
3.9 Classes of problems
3.10 Summary of chapter
3.11 Further reading
Part 2 Current Techniques
4 Probabilistic Approaches
4.1 Introduction to probability
4.2 Bayes' Theorem
4.3 Bayesian networks
4.4 Markov networks
4.5 References
5 Nearest Neighbour and Clustering Approaches
5.1 Introduction
5.2 Nearest neighbour method
5.3 Nearest neighbour approach for secondary structure protein folding prediction
5.4 Clustering
5.5 Advanced clustering techniques
5.6 Application guidelines
5.7 Summary of chapter
5.8 References
6 Identification (Decision) Trees
6.1 Method
6.2 Gain criterion
6.3 Over fitting and pruning
6.4 Application guidelines
6.5 Bioinformatics applications
6.6 Background
6.7 Summary of chapter
6.8 References
7 Neural Networks
7.1 Method
7.2 Application guidelines
7.3 Bioinformatics applications
7.4 Background
7.5
... mehr
Summary of chapter
7.6 References
8 Genetic Algorithms
8.1 Single-objective genetic algorithms - method
8.2 Single-objective genetic algorithms - example
8.3 Multi-objective genetic algorithms - method
8.4 Application guidelines
8.5 Genetic algorithms - bioinformatics applications
8.6 Summary of chapter
8.7 References and Further Reading
Part 3 Future Techniques
9 Genetic Programming
9.1 Method
9.2 Application guidelines
9.3 Bioinformatics applications
9.4 Background
9.5 Summary of chapter
9.6 References
10 Cellular Automata
10.1 Method
10.2 Application guidelines
10.3 Bioinformatics applications
10.4 Background
10.5 Summary of chapter
10.6 References and Further Reading
11 Hybrid Methods
11.1 Method
11.2 Neural-genetic algorithm for analyzing gene expression data
11.3 Genetic algorithm and k nearest neighbour hybrid for biochemistry solvation
11.4 Genetic programming neural networks for determining gene-gene interactions in epidemiology
11.5 Application guidelines
11.6 Conclusions
11.7 Summary of chapter
References and Further Reading
Index
7.6 References
8 Genetic Algorithms
8.1 Single-objective genetic algorithms - method
8.2 Single-objective genetic algorithms - example
8.3 Multi-objective genetic algorithms - method
8.4 Application guidelines
8.5 Genetic algorithms - bioinformatics applications
8.6 Summary of chapter
8.7 References and Further Reading
Part 3 Future Techniques
9 Genetic Programming
9.1 Method
9.2 Application guidelines
9.3 Bioinformatics applications
9.4 Background
9.5 Summary of chapter
9.6 References
10 Cellular Automata
10.1 Method
10.2 Application guidelines
10.3 Bioinformatics applications
10.4 Background
10.5 Summary of chapter
10.6 References and Further Reading
11 Hybrid Methods
11.1 Method
11.2 Neural-genetic algorithm for analyzing gene expression data
11.3 Genetic algorithm and k nearest neighbour hybrid for biochemistry solvation
11.4 Genetic programming neural networks for determining gene-gene interactions in epidemiology
11.5 Application guidelines
11.6 Conclusions
11.7 Summary of chapter
References and Further Reading
Index
... weniger
Bibliographische Angaben
- Autor: Ajit Narayanan
- 2005, 1. Auflage, 256 Seiten, Maße: 23,7 cm, Gebunden, Englisch
- Verlag: Wiley & Sons
- ISBN-10: 0470021756
- ISBN-13: 9780470021750
Sprache:
Englisch
Pressezitat
"... coverage of problems and techniques are such that more advanced practitioners might clearly find interest in parts of this book." (Genetic Programming in Evolvable Machinery , Oct 2006)
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