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Network-based Mathematical Modeling in Cell and Developmental Biology

Network-based Mathematical Modeling in Cell and Developmental Biology
Author: Susan Mertins
Publisher: Frontiers Media SA
Total Pages: 137
Release: 2024-08-22
Genre: Science
ISBN: 283255346X

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The vast amount of knowledge in Cell Signaling gathered through reductionist efforts and omics technology is poised to approach a Systems Biology understanding of precise representations of cell structure and function and predictions at multi-scale levels despite the complexity. Super-resolution microscopy and single cell analysis are also providing opportunities to explore both spatial and temporal landscapes. Notably, many basic biological processes have been studied capturing mechanistic detail with the goal to understand cellular proliferation and differentiation, gene regulation, morphogenesis, metabolism, and cell-cell communication. Similarly, at the intracellular level, addressing functions such as self-assembly, phase separation, and transport is leading to insights not readily understood as linear pathways. Therefore, network-based mathematical modeling, delineating dynamic biochemical reactions through ordinary and partial differential equations, promises to discover emergent biological properties not heretofore expected.


Multiscale Modeling of Developmental Systems

Multiscale Modeling of Developmental Systems
Author:
Publisher: Academic Press
Total Pages: 605
Release: 2007-12-18
Genre: Science
ISBN: 0080556531

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Mathematical and computational biology is playing an increasingly important role in the biological sciences. This science brings forward unique challenges, many of which are, at the moment, beyond the theoretical techniques available. Developmental biology, due to its complexity, has lagged somewhat behind its sister disciplines (such as molecular biology and population biology) in making use of quantitative modeling to further biological understanding. This volume comprises work that is among the best developmental modeling available and we feel it will do much to remedy this situation. This book is aimed at all those with an interest in the interdisciplinary field of computer and mathematical modeling of multi-cellular and developmental systems. It is also a goal of the Editors to attract more developmental biologists to consider integrating modeling components into their research. Most importantly, this book is intended to serve as a portal into this research area for younger scientists – especially graduate students and post-docs, from both biological and quantitative backgrounds. * Articles written by leading exponents in the field * Provides techniques to address multiscale modeling * Coverage includes a wide spectrum of modeling approaches * Includes descriptions of the most recent advances in the field


Mathematical Models in Developmental Biology

Mathematical Models in Developmental Biology
Author: Jerome K. Percus
Publisher: American Mathematical Soc.
Total Pages: 265
Release: 2015-06-19
Genre: Mathematics
ISBN: 147041080X

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The path from relatively unstructured egg to full organism is one of the most fascinating trajectories in the biological sciences. Its complexity calls for a very high level of organization, with an array of subprocesses in constant communication with each other. These notes introduce an interleaved set of mathematical models representative of research in the last few decades, as well as the techniques that have been developed for their solution. Such models offer an effective way of incorporating reliable data in a concise form, provide an approach complementary to the techniques of molecular biology, and help to inform and direct future research. Titles in this series are co-published with the Courant Institute of Mathematical Sciences at New York University.


Mathematical Modeling of Biological Systems, Volume I

Mathematical Modeling of Biological Systems, Volume I
Author: Andreas Deutsch
Publisher: Springer Science & Business Media
Total Pages: 378
Release: 2007-06-15
Genre: Mathematics
ISBN: 0817645586

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Volume I of this two-volume, interdisciplinary work is a unified presentation of a broad range of state-of-the-art topics in the rapidly growing field of mathematical modeling in the biological sciences. The chapters are thematically organized into the following main areas: cellular biophysics, regulatory networks, developmental biology, biomedical applications, data analysis and model validation. The work will be an excellent reference text for a broad audience of researchers, practitioners, and advanced students in this rapidly growing field at the intersection of applied mathematics, experimental biology and medicine, computational biology, biochemistry, computer science, and physics.


Mathematical Models of the Cell and Cell Associated Objects

Mathematical Models of the Cell and Cell Associated Objects
Author: Viktor V. Ivanov
Publisher: Elsevier
Total Pages: 355
Release: 2006-05-10
Genre: Computers
ISBN: 0080462723

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This book gives the reader a survey of hundreds results in the field of the cell and cell associated objects modeling. Applications to modeling in the areas of AIDS, cancers and life longevity are investigated in this book. Introduces and proves fundamental properties of evolutionary systems on optimal distribution of their various resources on their internal and external functions Gives detailed analysis of applications to modeling AIDS, cancers, and life longevity Introducing and grounding the respective numerical algorithms and software Detailed analysis of hundreds of scientific works in the field of mathematical modeling of the cell and cell associated objects


Simple Mathematical Models of Gene Regulatory Dynamics

Simple Mathematical Models of Gene Regulatory Dynamics
Author: Michael C. Mackey
Publisher: Springer
Total Pages: 128
Release: 2016-11-09
Genre: Medical
ISBN: 3319453181

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This is a short and self-contained introduction to the field of mathematical modeling of gene-networks in bacteria. As an entry point to the field, we focus on the analysis of simple gene-network dynamics. The notes commence with an introduction to the deterministic modeling of gene-networks, with extensive reference to applicable results coming from dynamical systems theory. The second part of the notes treats extensively several approaches to the study of gene-network dynamics in the presence of noise—either arising from low numbers of molecules involved, or due to noise external to the regulatory process. The third and final part of the notes gives a detailed treatment of three well studied and concrete examples of gene-network dynamics by considering the lactose operon, the tryptophan operon, and the lysis-lysogeny switch. The notes contain an index for easy location of particular topics as well as an extensive bibliography of the current literature. The target audience of these notes are mainly graduates students and young researchers with a solid mathematical background (calculus, ordinary differential equations, and probability theory at a minimum), as well as with basic notions of biochemistry, cell biology, and molecular biology. They are meant to serve as a readable and brief entry point into a field that is currently highly active, and will allow the reader to grasp the current state of research and so prepare them for defining and tackling new research problems.


A mathematical modeling framework to simulate and analyze cell type transitions

A mathematical modeling framework to simulate and analyze cell type transitions
Author: Daniella Schittler
Publisher: Logos Verlag Berlin GmbH
Total Pages: 192
Release: 2015-03-20
Genre: Mathematics
ISBN: 3832539352

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The quantitative understanding of changes in cell types, referred to as cell type transitions, is fundamental to advance fields such as stem cell research, immunology, and cancer therapies. This thesis provides a mathematical modeling framework to simulate and analyze cell type transitions. The novel methodological approaches and models presented here address diverse levels which are essential in this context: Gene regulatory network models represent the cell type-determining gene expression dynamics. Here, a novel construction method for gene regulatory network models is introduced, which allows to transfer results from generic low-dimensional to realistic high-dimensional gene regulatory network models. For populations of cells, a generalized model class is proposed that accounts for multiple cell types, division numbers, and the full label distribution. Analysis and solution methods are presented for this new model class, which cover common cell population experiments and allow to exploit the full information from data. The modeling and analysis methods presented here connect formerly isolated approaches, and thereby contribute to a holistic framework for the quantitative understanding of cell type transitions.


Pattern Formation in Morphogenesis

Pattern Formation in Morphogenesis
Author: Vincenzo Capasso
Publisher: Springer Science & Business Media
Total Pages: 283
Release: 2012-10-03
Genre: Mathematics
ISBN: 3642201636

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Pattern Formation in Morphogenesis is a rich source of interesting and challenging mathematical problems. The volume aims at showing how a combination of new discoveries in developmental biology and associated modelling and computational techniques has stimulated or may stimulate relevant advances in the field. Finally it aims at facilitating the process of unfolding a mutual recognition between Biologists and Mathematicians of their complementary skills, to the point where the resulting synergy generates new and novel discoveries. It offers an interdisciplinary interaction space between biologists from embryology, genetics and molecular biology who present their own work in the perspective of the advancement of their specific fields, and mathematicians who propose solutions based on the knowledge grasped from biologists.


Mathematical Modeling of Biological Systems, Volume II

Mathematical Modeling of Biological Systems, Volume II
Author: Andreas Deutsch
Publisher: Springer Science & Business Media
Total Pages: 383
Release: 2007-10-12
Genre: Mathematics
ISBN: 081764556X

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Volume II of this two-volume, interdisciplinary work is a unified presentation of a broad range of state-of-the-art topics in the rapidly growing field of mathematical modeling in the biological sciences. Highlighted throughout are mathematical and computational apporaches to examine central problems in the life sciences, ranging from the organization principles of individual cells to the dynamics of large populations. The chapters are thematically organized into the following main areas: epidemiology, evolution and ecology, immunology, neural systems and the brain, and innovative mathematical methods and education. The work will be an excellent reference text for a broad audience of researchers, practitioners, and advanced students in this rapidly growing field at the intersection of applied mathematics, experimental biology and medicine, computational biology, biochemistry, computer science, and physics.


Mathematical Modeling of Biological Systems, Volume II

Mathematical Modeling of Biological Systems, Volume II
Author: Andreas Deutsch
Publisher: Birkhäuser
Total Pages: 0
Release: 2007-10-12
Genre: Mathematics
ISBN: 9780817645564

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Volume II of this two-volume, interdisciplinary work is a unified presentation of a broad range of state-of-the-art topics in the rapidly growing field of mathematical modeling in the biological sciences. Highlighted throughout are mathematical and computational apporaches to examine central problems in the life sciences, ranging from the organization principles of individual cells to the dynamics of large populations. The chapters are thematically organized into the following main areas: epidemiology, evolution and ecology, immunology, neural systems and the brain, and innovative mathematical methods and education. The work will be an excellent reference text for a broad audience of researchers, practitioners, and advanced students in this rapidly growing field at the intersection of applied mathematics, experimental biology and medicine, computational biology, biochemistry, computer science, and physics.