Probabilistic Boolean Networks

Probabilistic Boolean Networks
Author: Ilya Shmulevich
Publisher: SIAM
Total Pages: 276
Release: 2010-01-21
Genre: Mathematics
ISBN: 0898716926

The first comprehensive treatment of probabilistic Boolean networks, unifying different strands of current research and addressing emerging issues.

Probabilistic Boolean Networks

Probabilistic Boolean Networks
Author: Ilya Shmulevich
Publisher: SIAM
Total Pages: 277
Release: 2010-01-01
Genre: Mathematics
ISBN: 0898717639

This is the first comprehensive treatment of probabilistic Boolean networks (PBNs), an important model class for studying genetic regulatory networks. This book covers basic model properties, including the relationships between network structure and dynamics, steady-state analysis, and relationships to other model classes." "Researchers in mathematics, computer science, and engineering are exposed to important applications in systems biology and presented with ample opportunities for developing new approaches and methods. The book is also appropriate for advanced undergraduates, graduate students, and scientists working in the fields of computational biology, genomic signal processing, control and systems theory, and computer science.

Analysis and Control of Boolean Networks

Analysis and Control of Boolean Networks
Author: Daizhan Cheng
Publisher: Springer Science & Business Media
Total Pages: 474
Release: 2010-11-23
Genre: Science
ISBN: 0857290975

Analysis and Control of Boolean Networks presents a systematic new approach to the investigation of Boolean control networks. The fundamental tool in this approach is a novel matrix product called the semi-tensor product (STP). Using the STP, a logical function can be expressed as a conventional discrete-time linear system. In the light of this linear expression, certain major issues concerning Boolean network topology – fixed points, cycles, transient times and basins of attractors – can be easily revealed by a set of formulae. This framework renders the state-space approach to dynamic control systems applicable to Boolean control networks. The bilinear-systemic representation of a Boolean control network makes it possible to investigate basic control problems including controllability, observability, stabilization, disturbance decoupling etc.

The Probabilistic Method

The Probabilistic Method
Author: Noga Alon
Publisher: John Wiley & Sons
Total Pages: 396
Release: 2015-11-02
Genre: Mathematics
ISBN: 1119062071

Praise for the Third Edition “Researchers of any kind of extremal combinatorics or theoretical computer science will welcome the new edition of this book.” - MAA Reviews Maintaining a standard of excellence that establishes The Probabilistic Method as the leading reference on probabilistic methods in combinatorics, the Fourth Edition continues to feature a clear writing style, illustrative examples, and illuminating exercises. The new edition includes numerous updates to reflect the most recent developments and advances in discrete mathematics and the connections to other areas in mathematics, theoretical computer science, and statistical physics. Emphasizing the methodology and techniques that enable problem-solving, The Probabilistic Method, Fourth Edition begins with a description of tools applied to probabilistic arguments, including basic techniques that use expectation and variance as well as the more advanced applications of martingales and correlation inequalities. The authors explore where probabilistic techniques have been applied successfully and also examine topical coverage such as discrepancy and random graphs, circuit complexity, computational geometry, and derandomization of randomized algorithms. Written by two well-known authorities in the field, the Fourth Edition features: Additional exercises throughout with hints and solutions to select problems in an appendix to help readers obtain a deeper understanding of the best methods and techniques New coverage on topics such as the Local Lemma, Six Standard Deviations result in Discrepancy Theory, Property B, and graph limits Updated sections to reflect major developments on the newest topics, discussions of the hypergraph container method, and many new references and improved results The Probabilistic Method, Fourth Edition is an ideal textbook for upper-undergraduate and graduate-level students majoring in mathematics, computer science, operations research, and statistics. The Fourth Edition is also an excellent reference for researchers and combinatorists who use probabilistic methods, discrete mathematics, and number theory. Noga Alon, PhD, is Baumritter Professor of Mathematics and Computer Science at Tel Aviv University. He is a member of the Israel National Academy of Sciences and Academia Europaea. A coeditor of the journal Random Structures and Algorithms, Dr. Alon is the recipient of the Polya Prize, The Gödel Prize, The Israel Prize, and the EMET Prize. Joel H. Spencer, PhD, is Professor of Mathematics and Computer Science at the Courant Institute of New York University. He is the cofounder and coeditor of the journal Random Structures and Algorithms and is a Sloane Foundation Fellow. Dr. Spencer has written more than 200 published articles and is the coauthor of Ramsey Theory, Second Edition, also published by Wiley.

Genomic Signal Processing

Genomic Signal Processing
Author: Ilya Shmulevich
Publisher: Princeton University Press
Total Pages: 314
Release: 2014-09-08
Genre: Science
ISBN: 1400865263

Genomic signal processing (GSP) can be defined as the analysis, processing, and use of genomic signals to gain biological knowledge, and the translation of that knowledge into systems-based applications that can be used to diagnose and treat genetic diseases. Situated at the crossroads of engineering, biology, mathematics, statistics, and computer science, GSP requires the development of both nonlinear dynamical models that adequately represent genomic regulation, and diagnostic and therapeutic tools based on these models. This book facilitates these developments by providing rigorous mathematical definitions and propositions for the main elements of GSP and by paying attention to the validity of models relative to the data. Ilya Shmulevich and Edward Dougherty cover real-world situations and explain their mathematical modeling in relation to systems biology and systems medicine. Genomic Signal Processing makes a major contribution to computational biology, systems biology, and translational genomics by providing a self-contained explanation of the fundamental mathematical issues facing researchers in four areas: classification, clustering, network modeling, and network intervention.

Control Theory and Systems Biology

Control Theory and Systems Biology
Author: Pablo A. Iglesias
Publisher: MIT Press
Total Pages: 359
Release: 2010
Genre: Biological control systems
ISBN: 0262013347

A survey of how engineering techniques from control and systems theory can be used to help biologists understand the behavior of cellular systems.

High-Dimensional Probability

High-Dimensional Probability
Author: Roman Vershynin
Publisher: Cambridge University Press
Total Pages: 299
Release: 2018-09-27
Genre: Business & Economics
ISBN: 1108415199

An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.

Introduction to Information Retrieval

Introduction to Information Retrieval
Author: Christopher D. Manning
Publisher: Cambridge University Press
Total Pages:
Release: 2008-07-07
Genre: Computers
ISBN: 1139472100

Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.

Foundations of Probabilistic Programming

Foundations of Probabilistic Programming
Author: Gilles Barthe
Publisher: Cambridge University Press
Total Pages: 583
Release: 2020-12-03
Genre: Computers
ISBN: 110848851X

This book provides an overview of the theoretical underpinnings of modern probabilistic programming and presents applications in e.g., machine learning, security, and approximate computing. Comprehensive survey chapters make the material accessible to graduate students and non-experts. This title is also available as Open Access on Cambridge Core.

Algebraic Shift Register Sequences

Algebraic Shift Register Sequences
Author: Mark Goresky
Publisher: Cambridge University Press
Total Pages: 515
Release: 2012-02-02
Genre: Computers
ISBN: 1107014999

Describes the design, mathematical analysis and implementation of pseudo-random sequences for applications in communications, cryptography and simulations.