Computational Techniques for Inferring Regulatory Networks PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Computational Techniques for Inferring Regulatory Networks PDF full book. Access full book title Computational Techniques for Inferring Regulatory Networks by Irene M. Ong. Download full books in PDF and EPUB format.
Author: Irene M. Ong
Publisher:
ISBN:
Category :
Languages : en
Pages : 144
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Book Description
Author: Irene M. Ong
Publisher:
ISBN:
Category :
Languages : en
Pages : 144
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Book Description
Author: Guido Sanguinetti
Publisher: Humana
ISBN: 9781493988815
Category : Science
Languages : en
Pages : 0
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Book Description
This volume explores recent techniques for the computational inference of gene regulatory networks (GRNs). The chapters in this book cover topics such as methods to infer GRNs from time-varying data; the extraction of causal information from biological data; GRN inference from multiple heterogeneous data sets; non-parametric and hybrid statistical methods; the joint inference of differential networks; and mechanistic models of gene regulation dynamics. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, descriptions of recently developed methods for GRN inference, applications of these methods on real and/ or simulated biological data, and step-by-step tutorials on the usage of associated software tools. Cutting-edge and thorough, Gene Regulatory Networks: Methods and Protocols is an essential tool for evaluating the current research needed to further address the common challenges faced by specialists in this field.
Author: Das, Sanjoy
Publisher: IGI Global
ISBN: 1605666866
Category : Computers
Languages : en
Pages : 740
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Book Description
"This book focuses on methods widely used in modeling gene networks including structure discovery, learning, and optimization"--Provided by publisher.
Author: Alberto Fuente
Publisher: Springer Science & Business Media
ISBN: 3642451616
Category : Science
Languages : en
Pages : 135
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Book Description
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.
Author: Eberhard O. Voit
Publisher: Cambridge University Press
ISBN: 9780521785792
Category : Medical
Languages : en
Pages : 556
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Book Description
Teaches the use of modern computational methods for the analysis of biomedical systems using case studies and accompanying software.
Author: Ilya Shmulevich
Publisher: SIAM
ISBN: 0898716926
Category : Mathematics
Languages : en
Pages : 276
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Book Description
The first comprehensive treatment of probabilistic Boolean networks, unifying different strands of current research and addressing emerging issues.
Author: Hamid Bolouri
Publisher: Imperial College Press
ISBN: 1848162200
Category : Medical
Languages : en
Pages : 341
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Book Description
This book serves as an introduction to the myriad computational approaches to gene regulatory modeling and analysis, and is written specifically with experimental biologists in mind. Mathematical jargon is avoided and explanations are given in intuitive terms. In cases where equations are unavoidable, they are derived from first principles or, at the very least, an intuitive description is provided. Extensive examples and a large number of model descriptions are provided for use in both classroom exercises as well as self-guided exploration and learning. As such, the book is ideal for self-learning and also as the basis of a semester-long course for undergraduate and graduate students in molecular biology, bioengineering, genome sciences, or systems biology.
Author:
Publisher: Academic Press
ISBN: 0123884217
Category : Science
Languages : en
Pages : 427
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Book Description
Computational methods are playing an ever increasing role in cell biology. This volume of Methods in Cell Biology focuses on Computational Methods in Cell Biology and consists of two parts: (1) data extraction and analysis to distill models and mechanisms, and (2) developing and simulating models to make predictions and testable hypotheses. - Focuses on computational methods in cell biology - Split into 2 parts--data extraction and analysis to distill models and mechanisms, and developing and simulating models to make predictions and testable hypotheses - Emphasizes the intimate and necessary connection with interpreting experimental data and proposing the next hypothesis and experiment
Author: Ying Xu
Publisher: World Scientific
ISBN: 1860949827
Category : Medical
Languages : en
Pages : 494
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Book Description
Over 500 prokaryotic genomes have been sequenced to date, and thousands more have been planned for the next few years. While these genomic sequence data provide unprecedented opportunities for biologists to study the world of prokaryotes, they also raise extremely challenging issues such as how to decode the rich information encoded in these genomes. This comprehensive volume includes a collection of cohesively written chapters on prokaryotic genomes, their organization and evolution, the information they encode, and the computational approaches needed to derive such information. A comparative view of bacterial and archaeal genomes, and how information is encoded differently in them, is also presented. Combining theoretical discussions and computational techniques, the book serves as a valuable introductory textbook for graduate-level microbial genomics and informatics courses.
Author: Hitoshi Iba
Publisher: John Wiley & Sons
ISBN: 1119079780
Category : Computers
Languages : en
Pages : 464
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Book Description
Introducing a handbook for gene regulatory network research using evolutionary computation, with applications for computer scientists, computational and system biologists This book is a step-by-step guideline for research in gene regulatory networks (GRN) using evolutionary computation (EC). The book is organized into four parts that deliver materials in a way equally attractive for a reader with training in computation or biology. Each of these sections, authored by well-known researchers and experienced practitioners, provides the relevant materials for the interested readers. The first part of this book contains an introductory background to the field. The second part presents the EC approaches for analysis and reconstruction of GRN from gene expression data. The third part of this book covers the contemporary advancements in the automatic construction of gene regulatory and reaction networks and gives direction and guidelines for future research. Finally, the last part of this book focuses on applications of GRNs with EC in other fields, such as design, engineering and robotics. • Provides a reference for current and future research in gene regulatory networks (GRN) using evolutionary computation (EC) • Covers sub-domains of GRN research using EC, such as expression profile analysis, reverse engineering, GRN evolution, applications • Contains useful contents for courses in gene regulatory networks, systems biology, computational biology, and synthetic biology • Delivers state-of-the-art research in genetic algorithms, genetic programming, and swarm intelligence Evolutionary Computation in Gene Regulatory Network Research is a reference for researchers and professionals in computer science, systems biology, and bioinformatics, as well as upper undergraduate, graduate, and postgraduate students. Hitoshi Iba is a Professor in the Department of Information and Communication Engineering, Graduate School of Information Science and Technology, at the University of Tokyo, Toyko, Japan. He is an Associate Editor of the IEEE Transactions on Evolutionary Computation and the journal of Genetic Programming and Evolvable Machines. Nasimul Noman is a lecturer in the School of Electrical Engineering and Computer Science at the University of Newcastle, NSW, Australia. From 2002 to 2012 he was a faculty member at the University of Dhaka, Bangladesh. Noman is an Editor of the BioMed Research International journal. His research interests include computational biology, synthetic biology, and bioinformatics.
