1 The Infogenomics Perspective 2 Basic Concepts 2.1 Sets and Relations 2.2 Strings and Rewriting 2.3 Variables and Distributions 2.4 Events and Probability 3 Information Theory 3.1 From Physical to Informational Entropy 3.2 Entropy and Computation 3.3 Entropic Concepts 3.

4 Codes 3.5 Huffman Encoding 3.6 First Shannon Theorem 3.7 Typical Sequences 3.8 Second Shannon Theorem 3.9 Signals and continuous distributions 3.10 Fourier Transform 3.11 Sampling Theorem 3.

12 Third Shannon Theorem 4 Informational Genomics 4.1 DNA Structure 4.2 Genome Texts 4.3 Genome Dictionaries 4.4 Genome Informational Indexes 4.5 Genome Information Sources 4.6 Genome Spectra 4.7 Elongation and Segmentation 4.

8 Genome Informational Laws 4.9 Genome complexity 4.10 Genome Divergences and Similarities 4.11 Lexicographic Ordering 4.12 Suffix Arrays ix x Contents 5 Information and Randomness 5.1 Topics in Probability Theory 5.2 Informational Randomness 5.3 Information in Physics 5.

4 The Informational Nature of Quantum Mechanics 6 Life Intelligence 6.1 Genetic algorithms 6.2 Swarm intelligence 6.3 Artificial neural networks 6.4 Artificial versus Human Intelligence 7 Introduction to Python 7.1 The Python language 7.2 The Python environment 7.3 Operators 7.

4 Statements 7.5 Functions 7.6 Collections 7.7 Sorting 7.8 Classes and Objects 7.9 Methods 7.10 Some notes on efficiency 7.11 Iterators 7.

12 Itertools 8 Laboratory in Python 8.1 Extraction of symbols 8.2 Extraction of words 8.3 Word multiplicity 8.4 Counting words 8.5 Searching for nullomers 8.6 Dictionary coverage 8.7 Reading FASTA files 8.

8 Informational indexes 8.9 Genomic distributions 8.10 Genomic data structures 8.11 Recurrence patterns 8.12 Generation of random genomes Index Acronyms References.