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Gene Regulatory Networks

Author: Guido Sanguinetti

Publisher: Humana

Published: 2018-12-14

Total Pages: 0

ISBN-13: 9781493988815

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.

Gene Network Inference

Author: Alberto Fuente

Publisher: Springer Science & Business Media

Published: 2014-01-03

Total Pages: 135

ISBN-13: 3642451616

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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.

Probabilistic Boolean Networks

Author: Ilya Shmulevich

Publisher: SIAM

Published: 2010-01-21

Total Pages: 276

ISBN-13: 0898716926

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The first comprehensive treatment of probabilistic Boolean networks, unifying different strands of current research and addressing emerging issues.

Weighted Network Analysis

Author: Steve Horvath

Publisher: Springer Science & Business Media

Published: 2011-04-30

Total Pages: 433

ISBN-13: 144198819X

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High-throughput measurements of gene expression and genetic marker data facilitate systems biologic and systems genetic data analysis strategies. Gene co-expression networks have been used to study a variety of biological systems, bridging the gap from individual genes to biologically or clinically important emergent phenotypes.

Network Inference in Molecular Biology

Author: Jesse M. Lingeman

Publisher: Springer Science & Business Media

Published: 2012-05-24

Total Pages: 106

ISBN-13: 1461431131

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Inferring gene regulatory networks is a difficult problem to solve due to the relative scarcity of data compared to the potential size of the networks. While researchers have developed techniques to find some of the underlying network structure, there is still no one-size-fits-all algorithm for every data set. Network Inference in Molecular Biology examines the current techniques used by researchers, and provides key insights into which algorithms best fit a collection of data. Through a series of in-depth examples, the book also outlines how to mix-and-match algorithms, in order to create one tailored to a specific data situation. Network Inference in Molecular Biology is intended for advanced-level students and researchers as a reference guide. Practitioners and professionals working in a related field will also find this book valuable.

Computational Intelligence and Bioinformatics

Author: De-Shuang Huang

Publisher: Springer

Published: 2006-09-01

Total Pages: 824

ISBN-13: 3540372822

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This book constitutes the refereed proceedings of the International Conference on Intelligent Computing, ICIC 2006, held in Kunming, China, in August 2006. The book presents 165 revised full papers, carefully reviewed. Topics covered include ant colony optimization, particle swarm optimization, swarm intelligence, autonomy-oriented computing, quantum and molecular computations, biological and DNA computing, intelligent computing in bioinformatics, intelligent computing in computational biology and drug design, computational genomics and proteomics, and more.

Drosophila Eye Development

Author: Kevin Moses

Publisher: Springer Science & Business Media

Published: 2002-03-12

Total Pages: 296

ISBN-13: 9783540425908

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1 Kevin Moses It is now 25 years since the study of the development of the compound eye in Drosophila really began with a classic paper (Ready et al. 1976). In 1864, August Weismann published a monograph on the development of Diptera and included some beautiful drawings of the developing imaginal discs (Weismann 1864). One of these is the first description of the third instar eye disc in which Weismann drew a vertical line separating a posterior domain that included a regular pattern of clustered cells from an anterior domain without such a pattern. Weismann suggested that these clusters were the precursors of the adult ommatidia and that the line marks the anterior edge of the eye. In his first suggestion he was absolutely correct - in his second he was wrong. The vertical line shown was not the anterior edge of the eye, but the anterior edge of a moving wave of patterning and cell type specification that 112 years later (1976) Ready, Hansen and Benzer would name the "morphogenetic furrow". While it is too late to hear from August Weismann, it is a particular pleasure to be able to include a chapter in this Volume from the first author of that 1976 paper: Don Ready! These past 25 years have seen an astonishing explosion in the study of the fly eye (see Fig.

Analysis of Microarray Data

Author: Matthias Dehmer

Publisher: John Wiley & Sons

Published: 2008-09-08

Total Pages: 438

ISBN-13: 3527622829

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This book is the first to focus on the application of mathematical networks for analyzing microarray data. This method goes well beyond the standard clustering methods traditionally used. From the contents: * Understanding and Preprocessing Microarray Data * Clustering of Microarray Data * Reconstruction of the Yeast Cell Cycle by Partial Correlations of Higher Order * Bilayer Verification Algorithm * Probabilistic Boolean Networks as Models for Gene Regulation * Estimating Transcriptional Regulatory Networks by a Bayesian Network * Analysis of Therapeutic Compound Effects * Statistical Methods for Inference of Genetic Networks and Regulatory Modules * Identification of Genetic Networks by Structural Equations * Predicting Functional Modules Using Microarray and Protein Interaction Data * Integrating Results from Literature Mining and Microarray Experiments to Infer Gene Networks The book is for both, scientists using the technique as well as those developing new analysis techniques.

Handbook of Research on Computational Methodologies in Gene Regulatory Networks

Author: Das, Sanjoy

Publisher: IGI Global

Published: 2009-10-31

Total Pages: 740

ISBN-13: 1605666866

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"This book focuses on methods widely used in modeling gene networks including structure discovery, learning, and optimization"--Provided by publisher.

Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applications

Author: K. G. Srinivasa

Publisher: Springer Nature

Published: 2020-01-30

Total Pages: 318

ISBN-13: 9811524459

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This book discusses topics related to bioinformatics, statistics, and machine learning, presenting the latest research in various areas of bioinformatics. It also highlights the role of computing and machine learning in knowledge extraction from biological data, and how this knowledge can be applied in fields such as drug design, health supplements, gene therapy, proteomics and agriculture.