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Genetics

Health, Medicine & Nursing

Gt Product Group

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B2B GT

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B2B & B2C

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.

Logic Synthesis for Genetic Diseases

POST SECONDARY FOUR YEAR

COLFR

COLSO

COLJR

COLSR

LOGIC SYNTHESIS FOR GENETIC DISEASES

Duration

Duration Unit Of Measure

Transaction Type

Front Cover.
Half Title Page.
Title Page.
Copyright Page.
Dedication.
Preface.
Acknowledgements.
Contents.
Acronyms.
List of Figures.
List of Tables.
1: Introduction.
2: Inference of Gene Regulatory Networks.
3: Predictor Set Inference using SAT.
4: Determining Gene Function in Boolean Networks using SAT.
5: Predictor Ranking using Modified Zhegalkin Functions.
6: Intervention of Gene Regulatory Networks.
7: ATPG for Cancer Therapy.
8: Summary and Future Work.
Index.

Logic Synthesis for Genetic Diseases.css-1p8rvzy{position:absolute;padding-left:8px;}

Logic Synthesis for Genetic Diseases