作者简介 杰拉德·(Gérard Battail)是法国国家高等通信学院的退休教授,法国有名的信息论和纠错编码专家,曾担任信息论领域靠前非常不错期刊IEEE Transactions on Information Theory的副主编。他在1997年退休以后开始致力于将信息论应用于自然科学,尤其是研究信息论和纠错编码在遗传和生物进化中的作用。
目录 Synthesis Lectures on Biomedical Engineering Contents Foreword Ⅰ An Informal Overview 1 Introduction 1.1 Genetics and communication engineering 1.2 Seeing heredity as a communication process 1.2.1 Main and subsidiary hypotheses 1.2.2 A static view of the living world: species and taxonomy 1.2.3 A dynamic view of the living world: evolution 1.3 Regeneration versus replication 2 A Brief Overview of Molecular Genetics 2.1 DNA structure and replication 2.2 DNA directs the construction of a phenotype 2.3 From DNA to protein,and from a genome to a phenotype 2.4 Genomes are very long 3 An Overview of Information Theory 3.1 Introduction 3.2 Shannons paradigm 3.3 Quantitative measurement of information 3.3.1 Single occurrence of events 3.3.2 Entropy of a source 3.3.3 Average m utual inform ation,capacity of a channel 3.4 Coding processes 3.4.1 Variants of Shannons paradigm 3.4.2 Source coding 3.4.3 Channel coding 3.4.4 Normalizing the blocks of Shannons paradigm 3.4.5 Fundamental theorems 3.5 A brief introduction to error-correcting codes 3.5.1 Redundant code,Hamming distance,and Hamming space 3.5.2 Reception in the presence of errors 3.6 Variant of Shannons paradigm intended to genetics 3.7 Computing an upper bound of DNA capacity 3.8 Summary of the next chapters Ⅱ Facts of Genetics and Information Theory 4 More on Molecular Genetics 4.1 Molecular memories: DNA and RNA 4.1.1 Unidimensional polymers as hereditary memories 4.1.2 Structure of double-strand DNA 4.1.3 RNA as another molecular memory 4.1.4 DNA as a long-lasting support of information 4.1.5 Error-correction coding as an implicit hypothesis 4.2 Place and function of DNA in the cell 4.2.1 Chromosomes and genomes 4.2.2 Principle of DNA replication 4.2.3 Genes instruct the synthesis of proteins 4.2.4 Amino-acids and polypeptidic chains 4.2.5 Synthesis of a polypeptidic chain 4.2.6 Proteins 4.3 Genome and phenotype 4.3.1 A genome instructs the development and maintenance of a phenotype 4.3.2 A phenotype hosts the genome from which it originates 4.4 DNA recombination and crossing over 5 More on Information Theory 5.1 Alphabet, sources, and entropy 5.1.1 Memoryless sources, Markovian sources, and their entropy 5.1.2 A fundamental property of stationary ergodic sources 5.2 About source coding 5.2.1 Source coding using a source extension 5.2.2 Kraft-McMillan inequality 5.2.3 Fundamental theorem of source coding 5.3 About channel coding 5.3.1 Fundamental theorem of channel coding 5.3.2 Coding for the binary sym metric channel 5.3.3 General case: Feinsteins lemma 5.4 Short introduction to algorithmic information theory 5.4.1 Principle of the algorithmic information theory 5.4.2 Algorithmic complexity and its relation to randomness and entropy 5.4.3 Sequences generated by random programs 5.5 Information and its relationship to semantics 5.6 Appendices 6 An Outline of Error-Correcting Codes 6.1 Introduction 6.2 Communicating a message through a channel 6.2.1 Defining a message 6.2.2 Describing a channel 6.3 Repetition as a means of error correction 6.3.1 Error patterns on repeated sym bols and their probability 6.3.2 Decision on a repeated symbol by majority voting 6.3.3 Soft decision on a repeated symbol 6.4 Encoding a full message 6.4.1 Introduction 6.4.2 A simple example 6.4.3 Decoding the code taken as example using the syndrome 6.4.4 Replication decoding of the code taken as example 6.4.5 Designing easily decodable codes: low-density parity check codes 6.4.6 Soft decoding of other block codes 6.5 Error-correcting codes within information theory 6.5.1 An outlook on the fundamental theorem of channel coding 6.5.2 A geometrical interpretation 6.5.3 Designing good error-correcting codes 6.6 Convolutional codes 6.6.1 Convolutional encoding 6.6.2 Systematic convolutional codes and their decoding 6.6.3 The trellis diagram and its use for decoding 6.7 Turbocodes 6.7.1 Description and properties 6.7.2 Symbol-by-symbol SISO decoding of turbocodes 6.7.3 Variants and comments 6.8 Historical outlook 6.9 Conclusion Ⅲ Necessity of Genomic Error Correcting Codes and its Consequences 7 DNA is an Ephemeral Memory 7.1 Probability of symbol erasure or substitution 7.1.1 Symbol erasure probability 7.1.2 Symbol substitution probability 7.2 Capacity computations 7.2.1 Capacity computations, single-strand DNA 7.2.2 Capacity computations, double-strand DNA 7.3 Estimating the error frequency before correction 7.4 Paradoxically, a permanent memory is ephemeral 8 A Toy Living World 8.1 A simple model 8.2 Computing statistical quantities 8.3 The initial memory content is progressively forgotten 8.4 Introducing natural selection in the toy living world 8.5 E xample of a toy living world using a very sim ple code 8.6 Evolution in the toy living world;phyletic graphs 9 Subsidiary Hypothesis, Nested System 9.1 Description of a nested system 9.2 Rate and length of component codes 9.3 Distances in the nested system 9.4 Consequences of the subsidiary hypothesis 10 Soft Codes 10.1 Introducing codes defined by a set of constraints 10.2 Genomic error-correcting codes as ‘soft codes’ 10.2.1 Defining soft codes 10.2.2 Identifying the alphabets 10.2.3 Potential genomic soft codes 10.3 Biological soft codes form nested systems 10.4 Further comments about genomic soft codes 10.5 Is a eukaryotic gene a systematic codeword 11 Biological Reality Conform s to the Hypotheses 11.1 Genomes are very redundant 11.2 Living beings belong to discrete species 11.2.1 A genomic error-correcting code implies discrete species 11.2.2 Species can be ordered according to a hierarchical taxonomy 11.2.3 Taxonomy and phylogeny 11.3 Necessity of successive regenerations 11.3.1 Correcting ability of genomic codes 11.3.2 N ature must proceed with successive regenerations 11.3.3 Joint implementation of replication and regeneration 11.4 Saltationism in evolution 11.4.1 Regeneration errors result in evolutive jumps 11.4.2 Saltationism depends on the layer depth in the nested system 11.5 Trend of evolution towards complexity 11.5.1 Evolutive advantage of long genomes 11.5.2 Increasing complexity results from lengthening genomes 11.6 Evolution is contingent 11.7 Relationship between genomes and phenotypes 11.7.1 Genome as specifying a phenotype 11.7.2 Neighborhood in genomic and phenotypic spaces 11.7.3 On genome comparisons expressed as percentages 12 Identification of Genomic Codes 12.1 Necessity of identifying genomic codes 12.1.1 An unusual approach 12.1.2 A necessary collaboration of engineers and biologists 12.2 Identifying error-correction means 12.2.1 Identifying an error-correcting code 12.2.2 Identifying component codes of the nested system 12.2.3 Identifying regeneration means 12.3 Genome distinction and conservation 12.4 Difficulties with sexual reproduction 13 Conclusion and Perspectives Bibliography Biography Index
以下为对购买帮助不大的评价