Infogenomics

ISBN-13: 9783031445002 / Angielski / Twarda / 2023

Vincenzo Manca;Vincenzo Bonnici

Opis

The book presents a conceptual and methodological basis for the mathematical and computational analysis of genomes.Genomes are containers of biological information, which direct the cell functions and the evolution of organisms. Combinatorial, probabilistic, and informational aspects are fundamental ingredients of any mathematical investigation of genomes aimed at providing mathematical principles for extracting the information that they contain.The topics presented in the book include research themes developed by authors in the last 15 years, and in many aspects, the book continues a preceding volume (Vincenzo Manca, Infobiotics: Information in biotic systems, Springer, 2013). The main inspiring idea of the book is an informational perspective to Genomics. Information is the most recent, among the fundamental mathematical and physical concepts developed in the last two centuries. It has revolutionized the whole science and continues, in this direction, to dominate the trends of the contemporary science. In fact, any discipline collects data from observations, by providing theories able to explain, predict, and dominate natural phenomena. But data are containers of information, whence information is essential in any scientific elaboration.Many open problems in deciphering genomes will be addressed, by showing an informational approach to the discovery of “genome languages”, according to which genomic texts are written. Life strategies, at many levels of organization, are encoded in these texts, and randomness has a crucial role in the birth and in the development of biological information, where the interplay of casualty and computation is probably the most secret key of life intelligence.

Spis treści

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.