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Handbook of research on computationa...
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Das, Sanjoy (1968-)
Handbook of research on computational methodologies in gene regulatory networks
紀錄類型:
書目-語言資料,印刷品 : 單行本
其他作者:
DasSanjoy, 1968-
其他團體作者:
IGI Global.
出版地:
Hershey, Pa.
出版者:
IGI Global;
出版年:
c2010.
面頁冊數:
electronic texts (xxix, 710 p. : ill.)digital files. :
標題:
Genetic regulation - Mathematical models -
標題:
Bayesian networks for modeling
標題:
Boolean networks
標題:
Computational approaches for modeling
標題:
Computational intelligence techniques
標題:
Gene regulatory networks
標題:
Genetical genomics data
標題:
Heterogeneous genetic networks
標題:
Markov decision process
標題:
Microarray gene expression measurements
標題:
Reverse engineering
電子資源:
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-60566-685-3
摘要註:
Recent advances in gene sequencing technology are now shedding light on the complex interplay between genes that elicit phenotypic behavior characteristic of any given organism. In order to mediate internal and external signals, the daunting task of classifying an organism's genes into complex signaling pathways needs to be completed. This book focuses on methods widely used in modeling gene networks including structure discovery, learning, and optimization. This innovative handbook of research presents a complete overview of computational intelligence approaches for learning and optimization and how they can be used in gene regulatory networks.
ISBN:
9781605666860
內容註:
What are Gene Regulatory Networks? / Alberto de la Fuente Introduction to GRNs / Ugo Ala, Christian Damasco Bayesian Networks for Modeling and Inferring Gene Regulatory Networks / Sebastian Bauer, Peter Robinson Inferring Gene Regulatory Networks from Genetical Genomics Data / Bing Liu, Ina Hoeschele, Alberto de la Fuente Inferring Genetic Regulatory Interactions with Bayesian Logic-Based Model / Svetlana Bulashevska A Bayes Regularized Ordinary Differential Equation Model for the Inference of Gene Regulatory Networks / Nicole Radde, Lars Kaderali Computational Approaches for Modeling Intrinsic Noise and Delays in Genetic Regulatory Networks / Manuel Barrio ... [et al.] Modeling Gene Regulatory Networks with Delayed Stochastic Dynamics / Andre S. Ribeiro, John J. Grefenstette, Stuart A. Kauffman Nonlinear Stochastic Differential Equations Method for Reverse Engineering of Gene Regulatory Network / Adriana Climescu-Haulica, Michelle Quirk Modelling Gene Regulatory Networks Using Computational Intelligence Techniques / Ramesh Ram, Madhu Chetty A Synthesis Method of Gene Regulatory Networks based on Gene Expression by Network Learning / Yoshihiro Mori, Yasuaki Kuroe Structural Learning of Genetic Regulatory Networks Based on Prior Biological Knowledge and Microarray Gene Expression Measurements / Yang Dai ... [et al.] Problems for Structure Learning: Aggregation and Computational Complexity / Frank Wimberly ... [et al.] Complexity of the BN and the PBN Models of GRNs and Mappings for Complexity Reduction / Ivan V. Iva Restricted to subscribers or individual electronic text purchasers.
Handbook of research on computational methodologies in gene regulatory networks
Handbook of research on computational methodologies in gene regulatory networks
/ [edited by] Sanjoy Das ... [et al.]. - Hershey, Pa. : IGI Global, c2010.. - electronic texts (xxix, 710 p. : ill.) ; digital files..
What are Gene Regulatory Networks? / Alberto de la Fuente.
Includes bibliographical references (p. 638-687) and index..
ISBN 9781605666860ISBN 1605666866ISBN 9781605666853ISBN 1605666858
Genetic regulation -- Mathematical models
Bayesian networks for modelingBoolean networksComputational approaches for modelingComputational intelligence techniquesGene regulatory networksGenetical genomics dataHeterogeneous genetic networksMarkov decision processMicroarray gene expression measurementsReverse engineering
Das, Sanjoy
Handbook of research on computational methodologies in gene regulatory networks
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What are Gene Regulatory Networks? / Alberto de la Fuente
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Introduction to GRNs / Ugo Ala, Christian Damasco
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Bayesian Networks for Modeling and Inferring Gene Regulatory Networks / Sebastian Bauer, Peter Robinson
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Inferring Gene Regulatory Networks from Genetical Genomics Data / Bing Liu, Ina Hoeschele, Alberto de la Fuente
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Inferring Genetic Regulatory Interactions with Bayesian Logic-Based Model / Svetlana Bulashevska
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A Bayes Regularized Ordinary Differential Equation Model for the Inference of Gene Regulatory Networks / Nicole Radde, Lars Kaderali
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Computational Approaches for Modeling Intrinsic Noise and Delays in Genetic Regulatory Networks / Manuel Barrio ... [et al.]
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Modeling Gene Regulatory Networks with Delayed Stochastic Dynamics / Andre S. Ribeiro, John J. Grefenstette, Stuart A. Kauffman
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Nonlinear Stochastic Differential Equations Method for Reverse Engineering of Gene Regulatory Network / Adriana Climescu-Haulica, Michelle Quirk
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Modelling Gene Regulatory Networks Using Computational Intelligence Techniques / Ramesh Ram, Madhu Chetty
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A Synthesis Method of Gene Regulatory Networks based on Gene Expression by Network Learning / Yoshihiro Mori, Yasuaki Kuroe
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Structural Learning of Genetic Regulatory Networks Based on Prior Biological Knowledge and Microarray Gene Expression Measurements / Yang Dai ... [et al.]
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Problems for Structure Learning: Aggregation and Computational Complexity / Frank Wimberly ... [et al.]
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Complexity of the BN and the PBN Models of GRNs and Mappings for Complexity Reduction / Ivan V. Iva
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Restricted to subscribers or individual electronic text purchasers.
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Recent advances in gene sequencing technology are now shedding light on the complex interplay between genes that elicit phenotypic behavior characteristic of any given organism. In order to mediate internal and external signals, the daunting task of classifying an organism's genes into complex signaling pathways needs to be completed. This book focuses on methods widely used in modeling gene networks including structure discovery, learning, and optimization. This innovative handbook of research presents a complete overview of computational intelligence approaches for learning and optimization and how they can be used in gene regulatory networks.
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http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-60566-685-3
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