Hugendubel.info - Die B2B Online-Buchhandlung 

Merkliste
Die Merkliste ist leer.
Bitte warten - die Druckansicht der Seite wird vorbereitet.
Der Druckdialog öffnet sich, sobald die Seite vollständig geladen wurde.
Sollte die Druckvorschau unvollständig sein, bitte schliessen und "Erneut drucken" wählen.

Intelligent Bioinformatics

E-BookPDF2 - DRM Adobe / Adobe Ebook ReaderE-Book
294 Seiten
Englisch
John Wiley & Sonserschienen am13.12.20051. Auflage
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.



Edward Keedwell is an Associate Professor in Computer Science. He joined the Computer Science discipline in 2006 having previously been a Research Fellow in the Centre for Water Systems and was appointed as a lecturer in Computer Science in 2009.

Ajit Narayanan is the inventor of FreeSpeech, a picture language with a deep grammatical structure. He's also the inventor of Avaz, India's first Augmentative and Alternative Communication device for children with disabilities.mehr
Verfügbare Formate
BuchGebunden
EUR159,50
E-BookPDF2 - DRM Adobe / Adobe Ebook ReaderE-Book
EUR125,99

Produkt

KlappentextBioinformatics 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.



Edward Keedwell is an Associate Professor in Computer Science. He joined the Computer Science discipline in 2006 having previously been a Research Fellow in the Centre for Water Systems and was appointed as a lecturer in Computer Science in 2009.

Ajit Narayanan is the inventor of FreeSpeech, a picture language with a deep grammatical structure. He's also the inventor of Avaz, India's first Augmentative and Alternative Communication device for children with disabilities.
Details
Weitere ISBN/GTIN9780470021767
ProduktartE-Book
EinbandartE-Book
FormatPDF
FormatFormat mit automatischem Seitenumbruch (reflowable)
Erscheinungsjahr2005
Erscheinungsdatum13.12.2005
Auflage1. Auflage
Seiten294 Seiten
SpracheEnglisch
Dateigrösse1100 Kbytes
Artikel-Nr.2768262
Rubriken
Genre9201

Inhalt/Kritik

Inhaltsverzeichnis
1;Intelligent Bioinformatics;3
1.1;Contents;7
1.2;Preface;11
1.3;Acknowledgement;13
1.4;PART 1 INTRODUCTION;15
1.4.1;1 Introduction to the Basics of Molecular Biology;17
1.4.1.1;1.1 Basic cell architecture;17
1.4.1.2;1.2 The structure, content and scale of deoxyribonucleic acid (DNA);18
1.4.1.3;1.3 History of the human genome;23
1.4.1.4;1.4 Genes and proteins;24
1.4.1.5;1.5 Current knowledge and the central dogma´;35
1.4.1.6;1.6 Why proteins are important;37
1.4.1.7;1.7 Gene and cell regulation;38
1.4.1.8;1.8 When cell regulation goes wrong;40
1.4.1.9;1.9 So, what is bioinformatics?;41
1.4.1.10;1.10 Summary of chapter;42
1.4.1.11;1.11 Further reading;43
1.4.2;2 Introduction to Problems and Challenges in Bioinformatics;45
1.4.2.1;2.1 Introduction;45
1.4.2.2;2.2 Genome;45
1.4.2.3;2.3 Transcriptome;54
1.4.2.4;2.4 Proteome;64
1.4.2.5;2.5 Interference technology, viruses and the immune system;71
1.4.2.6;2.6 Summary of chapter;77
1.4.2.7;2.7 Further reading;78
1.4.3;3 Introduction to Artificial Intelligence and Computer Science;79
1.4.3.1;3.1 Introduction to search;79
1.4.3.2;3.2 Search algorithms;80
1.4.3.3;3.3 Heuristic search methods;86
1.4.3.4;3.4 Optimal search strategies;90
1.4.3.5;3.5 Problems with search techniques;97
1.4.3.6;3.6 Complexity of search;98
1.4.3.7;3.7 Use of graphs in bioinformatics;100
1.4.3.8;3.8 Grammars, languages and automata;104
1.4.3.9;3.9 Classes of problems;110
1.4.3.10;3.10 Summary of chapter;112
1.4.3.11;3.11 Further reading;113
1.5;PART 2 CURRENT TECHNIQUES;115
1.5.1;4 Probabilistic Approaches;117
1.5.1.1;4.1 Introduction to probability;117
1.5.1.2;4.2 Bayes´ Theorem;119
1.5.1.3;4.3 Bayesian networks;125
1.5.1.4;4.4 Markov networks;130
1.5.1.5;4.5 Summary of chapter;139
1.5.1.6;4.6 References;140
1.5.2;5 Nearest Neighbour and Clustering Approaches;141
1.5.2.1;5.1 Introduction;141
1.5.2.2;5.2 Nearest neighbour method;144
1.5.2.3;5.3 Nearest neighbour approach for secondary structure protein folding prediction;146
1.5.2.4;5.4 Clustering;149
1.5.2.5;5.5 Advanced clustering techniques;152
1.5.2.6;5.6 Application guidelines;158
1.5.2.7;5.7 Summary of chapter;159
1.5.2.8;5.8 References;160
1.5.3;6 Identification (Decision) Trees;161
1.5.3.1;6.1 Method;161
1.5.3.2;6.2 Gain criterion;166
1.5.3.3;6.3 Over fitting and pruning;171
1.5.3.4;6.4 Application guidelines;174
1.5.3.5;6.5 Bioinformatics applications;177
1.5.3.6;6.6 Background;183
1.5.3.7;6.7 Summary of chapter;184
1.5.3.8;6.8 References;184
1.5.4;7 Neural Networks;187
1.5.4.1;7.1 Method;187
1.5.4.2;7.2 Application guidelines;199
1.5.4.3;7.3 Bioinformatics applications;201
1.5.4.4;7.4 Background;206
1.5.4.5;7.5 Summary of chapter;207
1.5.4.6;7.6 References;207
1.5.5;8 Genetic Algorithms;209
1.5.5.1;8.1 Single-objective genetic algorithms - method;209
1.5.5.2;8.2 Single-objective genetic algorithms - example;216
1.5.5.3;8.3 Multi-objective genetic algorithms - method;219
1.5.5.4;8.4 Application guidelines;221
1.5.5.5;8.5 Genetic algorithms - bioinformatics applications;224
1.5.5.6;8.6 Summary of chapter;231
1.5.5.7;8.7 References and further reading;231
1.6;PART 3 FUTURE TECHNIQUES;233
1.6.1;9 Genetic Programming;235
1.6.1.1;9.1 Method;235
1.6.1.2;9.2 Application guidelines;244
1.6.1.3;9.3 Bioinformatics applications;246
1.6.1.4;9.4 Background;250
1.6.1.5;9.5 Summary of chapter;250
1.6.1.6;9.6 References;251
1.6.2;10 Cellular Automata;253
1.6.2.1;10.1 Method;253
1.6.2.2;10.2 Application guidelines;259
1.6.2.3;10.3 Bioinformatics applications;261
1.6.2.4;10.4 Background;265
1.6.2.5;10.5 Summary of chapter;266
1.6.2.6;10.6 References and further reading;266
1.6.3;11 Hybrid Methods;269
1.6.3.1;11.1 Method;269
1.6.3.2;11.2 Neural-genetic algorithm for analysing gene expression data;270
1.6.3.3;11.3 Genetic algorithm and k nearest neighbour hybrid for biochemistry solvation;276
1.6.3.4;11.4 Genetic programming neural networks for determining gene - gene interactions in epidemiology;279
1.6.3.5;11.5 Application guidelines;282
1.6.3.6;11.6 Conclusions;282
1.6.3.7;11.7 Summary of chapter;283
1.6.3.8;11.8 References and further reading;283
1.7;Index;285mehr