Reverse Engineering Of Regulatory Networks
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Reverse Engineering Of Regulatory Networks
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Author : Sudip Mandal
language : en
Publisher: Springer Nature
Release Date : 2023-10-06
Reverse Engineering Of Regulatory Networks written by Sudip Mandal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-06 with Technology & Engineering categories.
This volume details the development of updated dry lab and wet lab based methods for the reconstruction of Gene regulatory networks (GRN). Chapters guide readers through culprit genes, in-silico drug discovery techniques, genome-wide ChIP-X data, high-Throughput Transcriptomic Data Exome Sequencing, Next-Generation Sequencing, Fuorescence Spectroscopy, data analysis in Bioinformatics, Computational Biology, and S-system based modeling of GRN. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Reverse Engineering of Regulatory Networks aims to be a useful and practical guide to new researchers and experts looking to expand their knowledge.
Towards Reverse Engineering Gene Regulatory Networks
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Author : Thomas Schlitt
language : en
Publisher:
Release Date : 2004
Towards Reverse Engineering Gene Regulatory Networks written by Thomas Schlitt and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.
Linking The Genes
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Author : ALBERTO. DE LA FUENTE
language : en
Publisher:
Release Date : 2018
Linking The Genes written by ALBERTO. DE LA FUENTE and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
Handbook Of Research On Computational Methodologies In Gene Regulatory Networks
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Author : Das, Sanjoy
language : en
Publisher: IGI Global
Release Date : 2009-10-31
Handbook Of Research On Computational Methodologies In Gene Regulatory Networks written by Das, Sanjoy and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-10-31 with Computers categories.
"This book focuses on methods widely used in modeling gene networks including structure discovery, learning, and optimization"--Provided by publisher.
Reverse Engineering Gene Regulatory Networks
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Author : Vincenzo Belcastro
language : en
Publisher:
Release Date : 2010
Reverse Engineering Gene Regulatory Networks written by Vincenzo Belcastro and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Genetic regulation categories.
Probabilistic Boolean Networks
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Author : Ilya Shmulevich
language : en
Publisher: SIAM
Release Date : 2010-01-01
Probabilistic Boolean Networks written by Ilya Shmulevich and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-01-01 with Mathematics categories.
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.
Proceedings Of The International Conference On Advanced Intelligent Systems And Informatics 2019
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Author : Aboul Ella Hassanien
language : en
Publisher: Springer Nature
Release Date : 2019-10-02
Proceedings Of The International Conference On Advanced Intelligent Systems And Informatics 2019 written by Aboul Ella Hassanien and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-02 with Technology & Engineering categories.
This book presents the proceedings of the 5th International Conference on Advanced Intelligent Systems and Informatics 2019 (AISI2019), which took place in Cairo, Egypt, from October 26 to 28, 2019. This international and interdisciplinary conference, which highlighted essential research and developments in the fields of informatics and intelligent systems, was organized by the Scientific Research Group in Egypt (SRGE). The book is divided into several sections, covering the following topics: machine learning and applications, swarm optimization and applications, robotic and control systems, sentiment analysis, e-learning and social media education, machine and deep learning algorithms, recognition and image processing, intelligent systems and applications, mobile computing and networking, cyber-physical systems and security, smart grids and renewable energy, and micro-grid and power systems.
Computational Evolution Of Neural And Morphological Development
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Author : Yaochu Jin
language : en
Publisher: Springer Nature
Release Date : 2023-07-14
Computational Evolution Of Neural And Morphological Development written by Yaochu Jin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-14 with Computers categories.
This book provides a basic yet unified overview of theory and methodologies for evolutionary developmental systems. Based on the author’s extensive research into the synergies between various approaches to artificial intelligence including evolutionary computation, artificial neural networks, and systems biology, it also examines the inherent links between biological intelligence and artificial intelligence. The book begins with an introduction to computational algorithms used to understand and simulate biological evolution and development, including evolutionary algorithms, gene regulatory network models, multi-cellular models for neural and morphological development, and computational models of neural plasticity. Chap. 2 discusses important properties of biological gene regulatory systems, including network motifs, network connectivity, robustness and evolvability. Going a step further, Chap. 3 presents methods for synthesizing regulatory motifs from scratch and creating more complex regulatory dynamics by combining basic regulatory motifs using evolutionary algorithms. Multi-cellular growth models, which can be used to simulate either neural or morphological development, are presented in Chapters 4 and 5. Chap. 6 examines the synergies and coupling between neural and morphological evolution and development. In turn, Chap. 7 provides preliminary yet promising examples of how evolutionary developmental systems can help in self-organized pattern generation, referred to as morphogenetic self-organization, highlighting the great potentials of evolutionary developmental systems. Finally, Chap. 8 rounds out the book, stressing the importance and promise of the evolutionary developmental approach to artificial intelligence. Featuring a wealth of diagrams, graphs and charts to aid in comprehension, this book offers a valuable asset for graduate students, researchers and practitioners who are interested in pursuing a different approach to artificial intelligence.
Handbook Of Statistical Systems Biology
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Author : Michael Stumpf
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-09
Handbook Of Statistical Systems Biology written by Michael Stumpf and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-09 with Science categories.
Systems Biology is now entering a mature phase in which the key issues are characterising uncertainty and stochastic effects in mathematical models of biological systems. The area is moving towards a full statistical analysis and probabilistic reasoning over the inferences that can be made from mathematical models. This handbook presents a comprehensive guide to the discipline for practitioners and educators, in providing a full and detailed treatment of these important and emerging subjects. Leading experts in systems biology and statistics have come together to provide insight in to the major ideas in the field, and in particular methods of specifying and fitting models, and estimating the unknown parameters. This book: Provides a comprehensive account of inference techniques in systems biology. Introduces classical and Bayesian statistical methods for complex systems. Explores networks and graphical modeling as well as a wide range of statistical models for dynamical systems. Discusses various applications for statistical systems biology, such as gene regulation and signal transduction. Features statistical data analysis on numerous technologies, including metabolic and transcriptomic technologies. Presents an in-depth presentation of reverse engineering approaches. Provides colour illustrations to explain key concepts. This handbook will be a key resource for researchers practising systems biology, and those requiring a comprehensive overview of this important field.
Gene Network Inference
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Author : Alberto Fuente
language : en
Publisher: Springer Science & Business Media
Release Date : 2014-01-03
Gene Network Inference written by Alberto Fuente and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-03 with Science categories.
This book presents recent methods for Systems Genetics (SG) data analysis, applying them to a suite of simulated SG benchmark datasets. Each of the chapter authors received the same datasets to evaluate the performance of their method to better understand which algorithms are most useful for obtaining reliable models from SG datasets. The knowledge gained from this benchmarking study will ultimately allow these algorithms to be used with confidence for SG studies e.g. of complex human diseases or food crop improvement. The book is primarily intended for researchers with a background in the life sciences, not for computer scientists or statisticians.