导语

  

内容提要

  

    遗传可被视为是极长时间尺度上的基因组信息传递。然而，基因组会在像人类生命这样短暂的时间尺度上产生偶发性错误（即突变），并可能导致显著的影响。香农1948年发表的《通信的数学原理》开创了信息论这一新领域，证明了通过一个不可靠（即可能出现错误）的信道进行可靠的信息传输是可能的，但能可靠传递的信息有一个容量，超过了这个极限，可靠通信就不再可能了。近年来随着Turbocodes等纠错编码的发明，在电子通信工程中以接近容量的方式可靠地传输信息已成为现实。我们日常生活的很多电子设备（如手机、CD、DVD、数字电视等）若没有高效的纠错码是无法工作的。遗传作为自然界在长久以前已解决的一个工程问题，也能用信息论的角度来研究。DNA的传输容量很容易以指数形式迅速衰减，这意味着必须使用纠错码来再生基因组，才能可靠地传递遗传信息。假设这样的纠错编码确实存在，就可以解释生命世界的基本特征，如分立物种及其等级分类，连续世代的必需性，甚至是向复杂生物进化的趋势。本书有两大目的，一是向遗传学家展示信息论和纠错编码是遗传信息传递的必要工具，还讨论了使用它们的一些生物学结果，并提出了基因编码的假设猜测。另一个目标是促使通信工程师对遗传学和生物学产生兴趣，以拓宽他们的视野，超越技术领域，向最杰出的工程师大自然学习。

    杰拉德·巴特尔（Gerard Battail）是法国国家高等通信学院的退休教授，法国著名的信息论和纠错编码专家，曾担任信息论领域国际权威期刊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。

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  Shannon's 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 Shannon's paradigm
      3.4.2  Source coding
      3.4.3  Channel coding
      3.4.4  Normalizing the blocks of Shannon's 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 Shannon's 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: Feinstein's 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