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Caltech researchers help unlock the secrets of gene regulatory networks
February 04, 2009
PASADENA, Calif.-- A quartet of studies by researchers at the California Institute of Technology (Caltech) highlight a special feature on gene regulatory networks recently published in the Proceedings of the National Academy of Sciences (PNAS). The collection of papers, "Gene Networks in Development and Evolution Special Feature, Sackler Colloquium," was coedited by Caltech's Eric H. Davidson, the Norman Chandler Professor of Cell Biology. His coeditor was Michael Levine, professor of genetics, genomics and development at the University of California, Berkeley. "The control system that determines how development of an animal occurs in each species is encoded in the genome, and the physical location of the sequences where this code is resident is being revealed in a new area of systems biology--the study of gene regulatory networks," says Davidson. Gene regulatory networks are the complex networks of gene interactions that direct the development of any given species. The papers in the collection focus on the gene regulatory networks of a variety of organisms, including fruit flies, soil-dwelling nematodes, sea urchins, lampreys, and mice. "These networks lie at the heart of the regulatory apparatus, and they consist of genes that encode proteins that regulate other genes, and the DNA sequences which control when and where they are expressed," says Davidson, who authored a paper in the special feature about a gene regulatory network found in sea urchin embryos. He and Levine also coauthored a perspective in the same issue of the journal on the properties of gene regulatory networks. In one paper, Ellen V. Rothenberg, one of the two Albert Billings Ruddock Professors of Biology at Caltech, examines, in mice, the intricate developmental pathway that causes blood stem cells to differentiate into T cells, a varied class of immune system cells that help the body fight off infection. The paper, Rothenberg says, represents a "codification of everything we know about T cell development. We've found that getting the right balances of the various regulatory signals is absolutely crucial for the T cells to come out right. It gives one a sense of how subtle and sophisticated the regulation can be." Another study in the special feature by Marianne Bronner-Fraser, the second Albert Billings Ruddock Professor of Biology, focuses on the gene regulatory network underlying neural crest formation in the lamprey, the most primitive living vertebrate. The neural crest is a group of embryonic cells that are pinched off during the formation of the neural tube--the precursor to the spinal cord--and then migrate throughout the developing body to form other nervous system structures. The study "reveals order and linkages within the network at early stages," Bronner-Fraser says. "Because the neural crest cell type represents a vertebrate innovation, our work in lampreys shows that this network is ancient and tightly conserved to the base of vertebrates," she says. The fourth of the Caltech papers, by Paul W. Sternberg, the Thomas Hunt Morgan Professor of Biology at Caltech and an investigator with the Howard Hughes Medical Institute (HHMI), and his colleagues, looks at a postembryonic gene regulatory network in Caenorhabditis elegans, a soil-dwelling worm commonly studied by developmental biologists. The gene regulatory network studied by Sternberg and his colleagues controls the formation of the worm's vulva, which connects the uterus with the outside and allows the passage of sperm and eggs. California Institute of Technology

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The Regulatory Genome: Gene Regulatory Networks In Development And Evolution
by Eric H. Davidson (Author)
Gene regulatory networks are the most complex, extensive control systems found in nature. The interaction between biology and evolution has been the subject of great interest in recent years. The author, Eric Davidson, has been instrumental in elucidating this relationship. He is a world renowned scientist and a major contributor to the field of developmental biology.
The Regulatory Genome beautifully explains the control of animal development in terms of structure/function relations of inherited regulatory DNA sequence, and the emergent properties of the gene regulatory networks composed of these sequences. New insights into the mechanisms of body plan evolution are derived from considerations of the consequences of change in developmental gene regulatory networks. Examples of...
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Gene Regulatory Networks: Methods and Protocols (Methods in Molecular Biology)
by Bart Deplancke (Editor), Nele Gheldof (Editor)
Gene regulatory networks play a vital role in organismal development and function by controlling gene expression. With the availability of complete genome sequences, several novel experimental and computational approaches have recently been developed which promise to significantly enhance our ability to comprehensively characterize these regulatory networks by enabling the identification of respectively their genomic or regulatory state components, or the interactions between these two in unprecedented detail. Divided into five convenient sections, Gene Regulatory Networks: Methods and Protocols details how each of these approaches contributes to a more thorough understanding of the composition and function of gene regulatory networks, while providing a comprehensive protocol on how to...
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Computational Modelling Of Gene Regulatory Networks -- A Primer
by Hamid Bolouri (Author)
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. Contents: Introduction; What...
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Probabilistic Boolean Networks: The Modeling and Control of Gene Regulatory Networks
by Ilya Shmulevich (Author), Edward R. Dougherty (Author)
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. It also discusses the inference of model parameters from experimental data and control strategies for driving network behavior towards desirable states. The PBN model is well suited to serve as a mathematical framework to study basic issues dealing with systems-based genomics, specifically, the relevant aspects of stochastic, nonlinear dynamical systems. The book builds a rigorous mathematical foundation for exploring these issues, which include long-run dynamical...
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Handbook of Research on Computational Methodologies in Gene Regulatory Networks
by Sanjoy Das (Author), Doina Caragea (Author), Stephen M. Welch (Author), William H. Hsu (Author), Sanjoy Das (Editor), Doina Caragea (Editor), Stephen M. Welch (Editor), William H. Hsu (Editor)
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 organisms genes into complex signaling pathways needs to be completed. The Handbook of Research on Computational Methodologies in Gene Regulatory Networks 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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Ingenious Genes: How Gene Regulation Networks Evolve to Control Development (Life and Mind: Philosophical Issues in Biology and Psychology)
by Roger Sansom (Author)
Each of us is a collection of more than ten trillion cells, busy performing tasks crucial to our continued existence. Gene regulation networks, consisting of a subset of genes called transcription factors, control cellular activity, producing the right gene activities for the many situations that the multiplicity of cells in our bodies face. Genes working together make up a truly ingenious system. In this book, Roger Sansom investigates how gene regulation works and how such a refined but simple system evolved. Sansom describes in detail two frameworks for understanding gene regulation. The first, developed by the theoretical biologist Stuart Kauffman, holds that...
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![Modeling gene regulatory networks with piecewise linear differential equations [An article from: European Journal of Operational Research]](http://ecx.images-amazon.com/images/I/51G4P0G7AGL._SX118__PC__PE00_.jpg)
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Modeling gene regulatory networks with piecewise linear differential equations [An article from: European Journal of Operational Research]
by J. Gebert (Author), N. Radde (Author), G.W. Weber (Author)
This digital document is a journal article from European Journal of Operational Research, published by Elsevier in 2007. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description: Microarray chips generate large amounts of data about a cell's state. In our work we want to analyze these data in order to describe the regulation processes within a cell. Therefore, we build a model which is capable of capturing the most relevant regulating interactions and present an approach how to calculate the parameters for the model from time-series data. This approach uses the discrete approximation method of least squares to solve a data fitting modeling problem. Furthermore, we...
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Network Inference in Molecular Biology: A Hands-on Framework (SpringerBriefs in Electrical and Computer Engineering)
by Jesse M. Lingeman (Author), Dennis Shasha (Author)
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...
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Gene Regulatory Networks Construction
by Fadhl Alakwaa (Author)
However the fast and development in DNA sequencing and high throughput technology, most of the simple biological process even in prokaryotic cells are not fully understood. This is because genes, as well as their products (proteins), do not work independently they interact with each other and form a complicated network which is called the Gene Regulatory Networks (GRN). GRN help us to understand the disease ontology and to reduce the cost of drug development. Recently, researchers from Caltech are able to answer some of the difficult and ambiguous biological questions by unlocking the Secrets of the Gene Regulatory Networks. During the last decade, many GRN construction algorithms have been developed. In this book, we simplified GRN construction steps; enumerate some of important...
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DNA Microarrays and Gene Expression: From Experiments to Data Analysis and Modeling
by Pierre Baldi (Author), G. Wesley Hatfield (Author)
Massive data acquisition technologies--such as genome sequencing, high-throughput drug screening, and DNA arrays--are in the process of revolutionizing biology and medicine. This concise, user-friendly and interdisciplinary guide to DNA microarray technology is an introduction and a reference for both biologists and computational scientists. The authors describe the underlying technologies and offer an awareness of the "noise" and pitfalls present in the data generated. They also provide an idea of the different data mining techniques and algorithms that are available to interpret data, and the advantages and disadvantages of each in differing situations.
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