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Logic Synthesis for Genetic Diseases de Pey-Chang Kent Lin

Logic Synthesis for Genetic Diseases

Autor Pey-Chang Kent Lin, Sunil P. Khatri
en Limba Engleză Paperback – 23 aug 2016
This book brings to bear a body of logic synthesis techniques, in order to contribute to the analysis and control of Boolean Networks (BN) for modeling genetic diseases such as cancer. The authors provide several VLSI logic techniques to model the genetic disease behavior as a BN, with powerful implicit enumeration techniques. Coverage also includes techniques from VLSI testing to control a faulty BN, transforming its behavior to a healthy BN, potentially aiding in efforts to find the best candidates for treatment of genetic diseases.
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Specificații

ISBN-13: 9781493955350
ISBN-10: 1493955357
Pagini: 100
Ilustrații: XXI, 100 p. 28 illus., 8 illus. in color.
Dimensiuni: 156 x 234 x 7 mm
Greutate: 0.19 kg
Ediția:Softcover Reprint of the Original 1st 2014 edition
Editura: Springer
Locul publicării:New York, NY, United States

Cuprins

Introduction.- Part I Inference of Gene Regulatory Networks.- Predictor Set Inference using SAT.- Determining Gene Function in Boolean Networks using SAT.- Predictor Ranking using Modified Zhegalkin Functions.- Part II Intervention of Gene Regulatory Networks.- ATPG for Cancer Therapy.- Summary and Future Work.

Textul de pe ultima copertă

This book brings to bear a body of logic synthesis techniques, in order to contribute to the analysis and control of Boolean Networks (BN) for modeling genetic diseases such as cancer. The authors provide several VLSI logic techniques to model the genetic disease behavior as a BN, with powerful implicit enumeration techniques. Coverage also includes techniques from VLSI testing to control a faulty BN, transforming its behavior to a healthy BN, potentially aiding in efforts to find the best candidates for treatment of genetic diseases. 
 
• Discusses a new application for logic synthesis, which enables the use of Boolean Networks to model the behavior of genetic-based diseases;
• Demonstrates how techniques such as Boolean Satisfiability (SAT) and Automatic Test Pattern Generation (ATPG) can be applied in the context of genetics;
• Provides content that appeals to researchers in genetics and logic synthesis and enables readers to make the connection between genetic diseases and logic techniques in a clear, unambiguous manner.

Caracteristici

Discusses a new application for logic synthesis, which enables the use of Boolean Networks to model the behavior of genetic-based diseases Demonstrates how techniques such as Boolean Satisfiability (SAT) and Automatic Test Pattern Generation (ATPG) can be applied in the context of genetics Provides content that appeals to researchers in genetics and logic synthesis and enables readers to make the connection between genetic diseases and logic techniques in a clear, unambiguous manner Includes supplementary material: sn.pub/extras