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Author : James M. Bower,Hamid Bolouri
Publisher : Unknown
Page : 128 pages
File Size : 50,5 Mb
Release : 2001
Category : Biochemistry
ISBN : OCLC:176049557
Author : James M. Bower,Hamid Bolouri
Publisher : MIT Press
Page : 386 pages
File Size : 51,9 Mb
Release : 2001
Category : Computers
ISBN : 0262524236
How new modeling techniques can be used to explore functionally relevant molecular and cellular relationships.
Author : James M. Bower
Publisher : Unknown
Page : 336 pages
File Size : 44,6 Mb
Release : 2004
Category : Biochemistry
ISBN : 818052051X
Author : Hamid Bolouri
Publisher : Imperial College Press
Page : 341 pages
File Size : 47,9 Mb
Release : 2008
Category : Medical
ISBN : 9781848162204
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 : Fabricio Alves Barbosa da Silva,Nicolas Carels,Marcelo Trindade dos Santos,Francisco José Pereira Lopes
Publisher : Springer Nature
Page : 381 pages
File Size : 54,9 Mb
Release : 2020-10-03
Category : Computers
ISBN : 9783030518622
This book presents a range of current research topics in biological network modeling, as well as its application in studies on human hosts, pathogens, and diseases. Systems biology is a rapidly expanding field that involves the study of biological systems through the mathematical modeling and analysis of large volumes of biological data. Gathering contributions from renowned experts in the field, some of the topics discussed in depth here include networks in systems biology, the computational modeling of multidrug-resistant bacteria, and systems biology of cancer. Given its scope, the book is intended for researchers, advanced students, and practitioners of systems biology. The chapters are research-oriented, and present some of the latest findings on their respective topics.
Author : Alpan Raval,Animesh Ray
Publisher : CRC Press
Page : 329 pages
File Size : 55,5 Mb
Release : 2016-04-19
Category : Computers
ISBN : 9781420010367
The new research area of genomics-inspired network biology lacks an introductory book that enables both physical/computational scientists and biologists to obtain a general yet sufficiently rigorous perspective of current thinking. Filling this gap, Introduction to Biological Networks provides a thorough introduction to genomics-inspired network bi
Author : Ralph-Johan Back,Corrado Priami,Ion Petre
Publisher : Springer
Page : 335 pages
File Size : 52,6 Mb
Release : 2009-10-01
Category : Computers
ISBN : 9783642041860
This issue on Computational Models for Cell Processes is based on a workshop that took place in Turku, Finland, May 2008. The papers span a mix of approaches to systems biology, ranging from quantitative techniques to computing paradigms inspired by biology.
Author : Seiya Imoto,Hiroshi Matsuno,Satoru Miyano
Publisher : Elsevier Inc. Chapters
Page : 548 pages
File Size : 52,8 Mb
Release : 2013-11-26
Category : Medical
ISBN : 9780128070079
This chapter describes the computational methods for estimating, modeling, and simulating biological systems. It also presents two approaches to understand biological systems and describes a method and a software tool developed by our research group. Bayesian network is a mathematical model for representing causal relationships among random variables by using conditional probabilities. The conditional probabilities describe the parent-child relationships and can be viewed as an extension of the deterministic models like Boolean networks. This model is suited for modeling qualitative relations between genes and allows mathematical and algorithmic analyses. We also devised a method to infer a gene network in terms of a linear system of differential equations from time-course gene expression data. A software tool is developed based on Petri net to modeling and simulation of gene networks. With this software tool, various models have been constructed and its utility has been demonstrated in practice.
Author : Das, Sanjoy,Caragea, Doina,Welch, Stephen,Hsu, William H.
Publisher : IGI Global
Page : 740 pages
File Size : 51,5 Mb
Release : 2009-10-31
Category : Computers
ISBN : 9781605666860
"This book focuses on methods widely used in modeling gene networks including structure discovery, learning, and optimization"--Provided by publisher.
Author : Sangdun Choi
Publisher : Springer Science & Business Media
Page : 900 pages
File Size : 50,8 Mb
Release : 2010-08-09
Category : Science
ISBN : 9781441957979
System Biology encompasses the knowledge from diverse fields such as Molecular Biology, Immunology, Genetics, Computational Biology, Mathematical Biology, etc. not only to address key questions that are not answerable by individual fields alone, but also to help in our understanding of the complexities of biological systems. Whole genome expression studies have provided us the means of studying the expression of thousands of genes under a particular condition and this technique had been widely used to find out the role of key macromolecules that are involved in biological signaling pathways. However, making sense of the underlying complexity is only possible if we interconnect various signaling pathways into human and computer readable network maps. These maps can then be used to classify and study individual components involved in a particular phenomenon. Apart from transcriptomics, several individual gene studies have resulted in adding to our knowledge of key components that are involved in a signaling pathway. It therefore becomes imperative to take into account of these studies also, while constructing our network maps to highlight the interconnectedness of the entire signaling pathways and the role of that particular individual protein in the pathway. This collection of articles will contain a collection of pioneering work done by scientists working in regulatory signaling networks and the use of large scale gene expression and omics data. The distinctive features of this book would be: Act a single source of information to understand the various components of different signaling network (roadmap of biochemical pathways, the nature of a molecule of interest in a particular pathway, etc.), Serve as a platform to highlight the key findings in this highly volatile and evolving field, and Provide answers to various techniques both related to microarray and cell signaling to the readers.
Author : Xiaobo Zhou,Stephen T. C. Wong
Publisher : World Scientific
Page : 398 pages
File Size : 46,7 Mb
Release : 2008
Category : Science
ISBN : 9789812707048
Computational systems biology is a new and rapidly developing field of research, concerned with understanding the structure and processes of biological systems at the molecular, cellular, tissue, and organ levels through computational modeling as well as novel information theoretic data and image analysis methods. By focusing on either information processing of biological data or on modeling physical and chemical processes of biosystems, and in combination with the recent breakthrough in deciphering the human genome, computational systems biology is guaranteed to play a central role in disease prediction and preventive medicine, gene technology and pharmaceuticals, and other biotechnology fields. This book begins by introducing the basic mathematical, statistical, and data mining principles of computational systems biology, and then presents bioinformatics technology in microarray and sequence analysis step-by-step. Offering an insightful look into the effectiveness of the systems approach in computational biology, it focuses on recurrent themes in bioinformatics, biomedical applications, and future directions for research.
Author : Ina Koch,Wolfgang Reisig,Falk Schreiber
Publisher : Springer Science & Business Media
Page : 378 pages
File Size : 43,9 Mb
Release : 2010-10-21
Category : Computers
ISBN : 9781849964746
The emerging, multi-disciplinary field of systems biology is devoted to the study of the relationships between various parts of a biological system, and computer modeling plays a vital role in the drive to understand the processes of life from an holistic viewpoint. Advancements in experimental technologies in biology and medicine have generated an enormous amount of biological data on the dependencies and interactions of many different molecular cell processes, fueling the development of numerous computational methods for exploring this data. The mathematical formalism of Petri net theory is able to encompass many of these techniques. This essential text/reference presents a comprehensive overview of cutting-edge research in applications of Petri nets in systems biology, with contributions from an international selection of experts. Those unfamiliar with the field are also provided with a general introduction to systems biology, the foundations of biochemistry, and the basics of Petri net theory. Further chapters address Petri net modeling techniques for building and analyzing biological models, as well as network prediction approaches, before reviewing the applications to networks of different biological classification. Topics and features: investigates the modular, qualitative modeling of regulatory networks using Petri nets, and examines an Hybrid Functional Petri net simulation case study; contains a glossary of the concepts and notation used in the book, in addition to exercises at the end of each chapter; covers the topological analysis of metabolic and regulatory networks, the analysis of models of signaling networks, and the prediction of network structure; provides a biological case study on the conversion of logical networks into Petri nets; discusses discrete modeling, stochastic modeling, fuzzy modeling, dynamic pathway modeling, genetic regulatory network modeling, and quantitative analysis techniques; includes a Foreword by Professor Jens Reich, Professor of Bioinformatics at Humboldt University and Max Delbrück Center for Molecular Medicine in Berlin. This unique guide to the modeling of biochemical systems using Petri net concepts will be of real utility to researchers and students of computational biology, systems biology, bioinformatics, computer science, and biochemistry.
Author : Reinhard Laubenbacher,Pedro Mendes
Publisher : Elsevier Inc. Chapters
Page : 548 pages
File Size : 49,7 Mb
Release : 2013-11-26
Category : Medical
ISBN : 9780128070123
Mathematical and statistical network modeling is an important step toward uncovering the organizational principles and dynamic behavior of biological networks. This chapter focuses on methods to construct discrete dynamic models of gene regulatory networks from experimental data sets, also sometimes referred to as top-down modeling or reverse engineering. Time-discrete dynamical systems models have long been used in biology, particularly in population dynamics. The models mainly focused on here are also assumed to have a finite set of possible states for each variable. That is, the modeling framework discussed in this chapter is that of time-discrete dynamical systems over a finite state set.
Author : Julien Delile,René Doursat,Nadine Peyriéras
Publisher : Elsevier Inc. Chapters
Page : 548 pages
File Size : 51,7 Mb
Release : 2013-11-26
Category : Medical
ISBN : 9780128070178
We propose a theoretical, yet realistic agent-based model and simulation platform of animal embryogenesis, called MecaGen, centered on the physico-chemical coupling of cell mechanics with gene expression and molecular signaling. This project aims to investigate the multiscale dynamics of the early stages of biological morphogenesis. Here, embryonic development is viewed as an emergent, self-organized phenomenon based on a myriad of cells and their genetically regulated, and regulating, biomechanical behavior. Cells’ mechanical properties (such as division rate, adhesion strength, or intrinsic motility) are closely correlated with their spatial location and temporal state of genetic and molecular dynamics (such as internal protein and external ligand concentrations) and affect each other concurrently. In a second part, we illustrate our model on artificial data (gene regulation motifs and cell sorting), then demonstrate a customization and application to a real biological case study in the zebrafish early development. We use as an example the episode of intercalation patterns appearing during the first phase of epiboly and the movements of the deep cells between the yolk and the enveloping layer. A domain of the model’s multidimensional parameter space is explored systematically, while experimental data obtained from microscopy imaging of live embryos is used to measure the “fitness” of the virtual embryo and validate our hypotheses.
Author : Wong Stephen Tin Chi,Zhou Xiaobo
Publisher : World Scientific Publishing Company
Page : 400 pages
File Size : 50,6 Mb
Release : 2008-01-02
Category : Science
ISBN : 9789813106994
Computational systems biology is a new and rapidly developing field of research, concerned with understanding the structure and processes of biological systems at the molecular, cellular, tissue, and organ levels through computational modeling as well as novel information theoretic data and image analysis methods. By focusing on either information processing of biological data or on modeling physical and chemical processes of biosystems, and in combination with the recent breakthrough in deciphering the human genome, computational systems biology is guaranteed to play a central role in disease prediction and preventive medicine, gene technology and pharmaceuticals, and other biotechnology fields.This book begins by introducing the basic mathematical, statistical, and data mining principles of computational systems biology, and then presents bioinformatics technology in microarray and sequence analysis step-by-step. Offering an insightful look into the effectiveness of the systems approach in computational biology, it focuses on recurrent themes in bioinformatics, biomedical applications, and future directions for research.