Probabilistic boolean networks - Info and Reading Options
the modeling and control of gene regulatory networks
By Ilya Shmulevich
"Probabilistic boolean networks" was published by Society for Industrial and Applied Mathematics in 2010 - Philadelphia, it has 267 pages and the language of the book is English.
“Probabilistic boolean networks” Metadata:
- Title: Probabilistic boolean networks
- Author: Ilya Shmulevich
- Language: English
- Number of Pages: 267
- Publisher: ➤ Society for Industrial and Applied Mathematics
- Publish Date: 2010
- Publish Location: Philadelphia
“Probabilistic boolean networks” Subjects and Themes:
- Subjects: Genetic regulation - Computer simulation - Gene regulatory networks - Statistical Models - Genetic Models
Edition Specifications:
- Pagination: p. ;
Edition Identifiers:
- The Open Library ID: OL24013296M - OL16686162W
- Online Computer Library Center (OCLC) ID: 434319365
- Library of Congress Control Number (LCCN): 2009034643
- ISBN-13: 9780898716924 - 9780898717631
- All ISBNs: 9780898716924 - 9780898717631
AI-generated Review of “Probabilistic boolean networks”:
"Probabilistic boolean networks" Table Of Contents:
- 1- Boolean networks
- 2- Structure and dynamics of probabilistic boolean networks
- 3- Inference of model structure
- 4- Structural intervention
- 5- External control
- 6- Asynchronous networks.
"Probabilistic boolean networks" Description:
The Open Library:
"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 bookis 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."--Jacket.
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