Single-Cell-Based Models in Biology and Medicine PDF Download
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Author: Alexander Anderson
Publisher: Springer Science & Business Media
ISBN: 376438123X
Category : Mathematics
Languages : en
Pages : 346
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Book Description
Aimed at postgraduate students in a variety of biology-related disciplines, this volume presents a collection of mathematical and computational single-cell-based models and their application. The main sections cover four general model groupings: hybrid cellular automata, cellular potts, lattice-free cells, and viscoelastic cells. Each section is introduced by a discussion of the applicability of the particular modelling approach and its advantages and disadvantages, which will make the book suitable for students starting research in mathematical biology as well as scientists modelling multicellular processes.
Author: Alexander Anderson
Publisher: Springer Science & Business Media
ISBN: 376438123X
Category : Mathematics
Languages : en
Pages : 346
Get Book Here
Book Description
Aimed at postgraduate students in a variety of biology-related disciplines, this volume presents a collection of mathematical and computational single-cell-based models and their application. The main sections cover four general model groupings: hybrid cellular automata, cellular potts, lattice-free cells, and viscoelastic cells. Each section is introduced by a discussion of the applicability of the particular modelling approach and its advantages and disadvantages, which will make the book suitable for students starting research in mathematical biology as well as scientists modelling multicellular processes.
Author:
Publisher:
ISBN: 9780815332183
Category : Cells
Languages : en
Pages : 0
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Book Description
Author: William L. William L. Hamilton
Publisher: Springer Nature
ISBN: 3031015886
Category : Computers
Languages : en
Pages : 141
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Book Description
Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.
Author: Marie Davidian
Publisher: Routledge
ISBN: 1351428152
Category : Mathematics
Languages : en
Pages : 360
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Book Description
Nonlinear measurement data arise in a wide variety of biological and biomedical applications, such as longitudinal clinical trials, studies of drug kinetics and growth, and the analysis of assay and laboratory data. Nonlinear Models for Repeated Measurement Data provides the first unified development of methods and models for data of this type, with a detailed treatment of inference for the nonlinear mixed effects and its extensions. A particular strength of the book is the inclusion of several detailed case studies from the areas of population pharmacokinetics and pharmacodynamics, immunoassay and bioassay development and the analysis of growth curves.
Author: Guo-Cheng Yuan
Publisher: Humana Press
ISBN: 9781493990566
Category : Science
Languages : en
Pages : 271
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Book Description
This detailed book provides state-of-art computational approaches to further explore the exciting opportunities presented by single-cell technologies. Chapters each detail a computational toolbox aimed to overcome a specific challenge in single-cell analysis, such as data normalization, rare cell-type identification, and spatial transcriptomics analysis, all with a focus on hands-on implementation of computational methods for analyzing experimental data. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Computational Methods for Single-Cell Data Analysis aims to cover a wide range of tasks and serves as a vital handbook for single-cell data analysis.
Author: Patrick Cahan
Publisher: Humana
ISBN: 9781493992232
Category : Science
Languages : en
Pages : 0
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Book Description
This volume details methods and protocols to further the study of stem cells within the computational stem cell biology (CSCB) field. Chapters are divided into four sections covering the theory and practice of modeling of stem cell behavior, analyzing single cell genome-scale measurements, reconstructing gene regulatory networks, and metabolomics. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Computational Stem Cell Biology: Methods and Protocols will be an invaluable guide to researchers as they explore stem cells from the perspective of computational biology.
Author: Alessandro Minelli
Publisher: Oxford University Press, USA
ISBN: 0199671435
Category : Science
Languages : en
Pages : 299
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Book Description
Is it possible to explain and predict the development of living things? What is development? Articulate answers to these seemingly innocuous questions are far from straightforward. To date, no systematic, targeted effort has been made to construct a unifying theory of development. This novel work offers a unique exploration of the foundations of ontogeny by asking how the development of living things should be understood. It explores the key concepts of developmental biology, asks whether general principles of development can be discovered, and examines the role of models and theories. The two editors (one a biologist with long interest in the theoretical aspects of his discipline, the other a philosopher of science who has mainly worked on biological systems) have assembled a team of leading contributors who are representative of the scientific and philosophical community within which a diversity of thoughts are growing, and out of which a theory of development may eventually emerge. They analyse a wealth of approaches to concepts, models and theories of development, such as gene regulatory networks, accounts based on systems biology and on physics of soft matter, the different articulations of evolution and development, symbiont-induced development, as well as the widely discussed concepts of positional information and morphogenetic field, the idea of a 'programme' of development and its critiques, and the long-standing opposition between preformationist and epigenetic conceptions of development. Towards a Theory of Development is primarily aimed at students and researchers in the fields of 'evo-devo', developmental biology, theoretical biology, systems biology, biophysics, and the philosophy of science.
Author: Ron Milo
Publisher: Garland Science
ISBN: 1317230698
Category : Science
Languages : en
Pages : 399
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Book Description
A Top 25 CHOICE 2016 Title, and recipient of the CHOICE Outstanding Academic Title (OAT) Award. How much energy is released in ATP hydrolysis? How many mRNAs are in a cell? How genetically similar are two random people? What is faster, transcription or translation?Cell Biology by the Numbers explores these questions and dozens of others provid
Author: Marco Scianna
Publisher: CRC Press
ISBN: 1466514795
Category : Mathematics
Languages : en
Pages : 300
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Book Description
This work shows how the cellular Potts model can be used as a framework for model building and how extended models can achieve even better biological practicality, accuracy, and predictive power. It focuses on ways to integrate and interface the basic cellular Potts model at the mesoscopic scale with approaches that accurately model microscopic dynamics. These extensions are designed to create a nested and hybrid environment, where the evolution of a biological system is realistically driven by the constant interplay and flux of information between the different levels of description.
Author: Greg Conradi Smith
Publisher: Cambridge University Press
ISBN: 1107005361
Category : Mathematics
Languages : en
Pages : 395
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Book Description
What every neuroscientist should know about the mathematical modeling of excitable cells, presented at an introductory level.
