Download or read book Modeling and Parameter Estimation for Heterogeneous Cell Populations written by Jan Hasenauer and published by Logos Verlag Berlin GmbH. This book was released on 2013 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most of the modeling performed in biology aims at achieving a quantitative description and understanding of the intracellular signaling pathways within a "typical cell". However, in many biologically important situations even genetically identical cell populations show a heterogeneous response. This means that individual members of the cell population behave differently. Such situations require the study of cell-to-cell variability and the development of models for heterogeneous cell populations. The main contribution of this thesis is the development of unifying modeling frameworks for signal transduction and proliferation processes in heterogeneous cell populations. These modeling frameworks allow for the detailed description of individual cells as well as differences between them. In contrast to many existing modeling approaches, the proposed frameworks allow for a direct comparison of model predictions with available data. Beyond this, the proposed population models can be simulated efficiently and, by exploiting the model structures, we are able to develop model-tailored Bayesian parameter estimation methods. These methods enable the calculation of the optimal parameter estimates, as well as the evaluation of the parameter and prediction uncertainties. The proposed tools allow for novel insights in population dynamics, in particular the model-based characterization of population heterogeneity and cellular subgroups. This is illustrated for two different application examples: pro- and anti-apoptotic signaling, which is interesting in the context of cancer therapy, and immune cell proliferation.
Download or read book A mathematical modeling framework to simulate and analyze cell type transitions written by Daniella Schittler and published by Logos Verlag Berlin GmbH. This book was released on 2015-03-20 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Network Bioscience 2nd Edition written by Marco Pellegrini and published by Frontiers Media SA. This book was released on 2020-03-27 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Network science has accelerated a deep and successful trend in research that influences a range of disciplines like mathematics, graph theory, physics, statistics, data science and computer science (just to name a few) and adapts the relevant techniques and insights to address relevant but disparate social, biological, technological questions. We are now in an era of 'big biological data' supported by cost-effective high-throughput genomic, transcriptomic, proteomic, metabolomic data collection techniques that allow one to take snapshots of the cells' molecular profiles in a systematic fashion. Moreover recently, also phenotypic data, data on diseases, symptoms, patients, etc. are being collected at nation-wide level thus giving us another source of highly related (causal) 'big data'. This wealth of data is usually modeled as networks (aka binary relations, graphs or webs) of interactions, (including protein-protein, metabolic, signaling and transcription-regulatory interactions). The network model is a key view point leading to the uncovering of mesoscale phenomena, thus providing an essential bridge between the observable phenotypes and 'omics' underlying mechanisms. Moreover, network analysis is a powerful 'hypothesis generation' tool guiding the scientific cycle of 'data gathering', 'data interpretation, 'hypothesis generation' and 'hypothesis testing'. A major challenge in contemporary research is the synthesis of deep insights coming from network science with the wealth of data (often noisy, contradictory, incomplete and difficult to replicate) so to answer meaningful biological questions, in a quantifiable way using static and dynamic properties of biological networks.
Download or read book Computational Methods in Systems Biology written by Ezio Bartocci and published by Springer. This book was released on 2016-09-03 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 14th International Conference on Computational Methods in Systems Biology, CMSB 2016, held in Cambridge, UK, in September 2016. The 20 full papers, 3 tool papers and 9 posters presented were carefully reviewed and selected from 37 regular paper submissions. The topics include formalisms for modeling biological processes; models and their biological applications; frameworks for model verification, validation, analysis, and simulation of biological systems; high-performance computational systems biology and parallel implementations; model inference from experimental data; model integration from biological databases; multi-scale modeling and analysis methods; and computational approaches for synthetic biology.
Download or read book Managing Complexity Reducing Perplexity written by Marcello Delitala and published by Springer. This book was released on 2014-06-04 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: ”Managing Complexity, Reducing Perplexity” is devoted to an overview of the status of the art in the study of complex systems, with particular focus on the analysis of systems pertaining to living matter. Both senior scientists and young researchers from diverse and prestigious institutions with a deliberately interdisciplinary cut were invited, in order to compare approaches and problems from different disciplines. The common aim of the contributions was to analyze the complexity of living systems by means of new mathematical paradigms that are more adherent to reality and which are able to generate both exploratory and predictive models that are capable of achieving a deeper insight into life science phenomena.
Download or read book Population Parameters written by Hamish McCallum and published by John Wiley & Sons. This book was released on 2008-04-15 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ecologists and environmental managers rely on mathematical models, both to understand ecological systems and to predict future system behavior. In turn, models rely on appropriate estimates of their parameters. This book brings together a diverse and scattered literature, to provide clear guidance on how to estimate parameters for models of animal populations. It is not a recipe book of statistical procedures. Instead, it concentrates on how to select the best approach to parameter estimation for a particular problem, and how to ensure that the quality estimated is the appropriate one for the specific purpose of the modelling exercise. Commencing with a toolbox of useful generic approaches to parameter estimation, the book deals with methods for estimating parameters for single populations. These parameters include population size, birth and death rates, and the population growth rate. For such parameters, rigorous statistical theory has been developed, and software is readily available. The problem is to select the optimal sampling design and method of analysis. The second part of the book deals with parameters that describe spatial dynamics, and ecological interactions such as competition, predation and parasitism. Here the principle problems are designing appropriate experiments and ensuring that the quantities measured by the experiments are relevant to the ecological models in which they will be used. This book will be essential reading for ecological researchers, postgraduate students and environmental managers who need to address an ecological problem through a population model. It is accessible to anyone with an understanding of basic statistical methods and population ecology. Unique in concentrating on parameter estimation within modelling. Fills a glaring gap in the literature. Not too technical, so suitable for the statistically inept. Methods explained in algebra, but also in worked examples using commonly available computer packages (SAS, GLIM, and some more specialised packages where relvant). Some spreadsheet based examples also included.
Download or read book Mathematical Modeling of the Immune System in Homeostasis Infection and Disease written by Gennady Bocharov and published by Frontiers Media SA. This book was released on 2020-02-24 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: The immune system provides the host organism with defense mechanisms against invading pathogens and tumor development and it plays an active role in tissue and organ regeneration. Deviations from the normal physiological functioning of the immune system can lead to the development of diseases with various pathologies including autoimmune diseases and cancer. Modern research in immunology is characterized by an unprecedented level of detail that has progressed towards viewing the immune system as numerous components that function together as a whole network. Currently, we are facing significant difficulties in analyzing the data being generated from high-throughput technologies for understanding immune system dynamics and functions, a problem known as the ‘curse of dimensionality’. As the mainstream research in mathematical immunology is based on low-resolution models, a fundamental question is how complex the mathematical models should be? To respond to this challenging issue, we advocate a hypothesis-driven approach to formulate and apply available mathematical modelling technologies for understanding the complexity of the immune system. Moreover, pure empirical analyses of immune system behavior and the system’s response to external perturbations can only produce a static description of the individual components of the immune system and the interactions between them. Shifting our view of the immune system from a static schematic perception to a dynamic multi-level system is a daunting task. It requires the development of appropriate mathematical methodologies for the holistic and quantitative analysis of multi-level molecular and cellular networks. Their coordinated behavior is dynamically controlled via distributed feedback and feedforward mechanisms which altogether orchestrate immune system functions. The molecular regulatory loops inherent to the immune system that mediate cellular behaviors, e.g. exhaustion, suppression, activation and tuning, can be analyzed using mathematical categories such as multi-stability, switches, ultra-sensitivity, distributed system, graph dynamics, or hierarchical control. GB is supported by the Russian Science Foundation (grant 18-11-00171). AM is also supported by grants from the Spanish Ministry of Economy, Industry and Competitiveness and FEDER grant no. SAF2016-75505-R, the “María de Maeztu” Programme for Units of Excellence in R&D (MDM-2014-0370) and the Russian Science Foundation (grant 18-11-00171).
Download or read book Systems Immunology written by Jayajit Das and published by CRC Press. This book was released on 2018-09-03 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Taken together, the body of information contained in this book provides readers with a bird’s-eye view of different aspects of exciting work at the convergence of disciplines that will ultimately lead to a future where we understand how immunity is regulated, and how we can harness this knowledge toward practical ends that reduce human suffering. I commend the editors for putting this volume together." –Arup K. Chakraborty, Robert T. Haslam Professor of Chemical Engineering, and Professor of Physics, Chemistry, and Biological Engineering, Massachusetts Institute of Technology, Cambridge, USA New experimental techniques in immunology have produced large and complex data sets that require quantitative modeling for analysis. This book provides a complete overview of computational immunology, from basic concepts to mathematical modeling at the single molecule, cellular, organism, and population levels. It showcases modern mechanistic models and their use in making predictions, designing experiments, and elucidating underlying biochemical processes. It begins with an introduction to data analysis, approximations, and assumptions used in model building. Core chapters address models and methods for studying immune responses, with fundamental concepts clearly defined. Readers from immunology, quantitative biology, and applied physics will benefit from the following: Fundamental principles of computational immunology and modern quantitative methods for studying immune response at the single molecule, cellular, organism, and population levels. An overview of basic concepts in modeling and data analysis. Coverage of topics where mechanistic modeling has contributed substantially to current understanding. Discussion of genetic diversity of the immune system, cell signaling in the immune system, immune response at the cell population scale, and ecology of host-pathogen interactions.
Download or read book Biological Networks written by Rudiyanto Gunawan and published by MDPI. This book was released on 2019-01-10 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Biological Networks" that was published in Processes
Download or read book Dynamics and Control of Process Systems 2004 written by Sirish Shah and published by Elsevier. This book was released on 2005-06-10 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Mathematical Biology II written by James D. Murray and published by Springer Science & Business Media. This book was released on 2011-02-15 with total page 834 pages. Available in PDF, EPUB and Kindle. Book excerpt: This richly illustrated third edition provides a thorough training in practical mathematical biology and shows how exciting mathematical challenges can arise from a genuinely interdisciplinary involvement with the biosciences. It has been extensively updated and extended to cover much of the growth of mathematical biology. From the reviews: ""This book, a classical text in mathematical biology, cleverly combines mathematical tools with subject area sciences."--SHORT BOOK REVIEWS
Download or read book Mathematical Modeling of NF B and p53 Signaling in the DNA Damage Response written by Fabian Konrath and published by Logos Verlag Berlin GmbH. This book was released on 2020-07-24 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cells are permanently challenged by DNA damage which can be induced by environmental factors such as UV irradiation or intracellular factors like reactive oxygen species. As damaged DNA can lead to malignant transformations, a complex signaling network termed DNA damage response is activated upon detection of DNA lesions and allows to maintain genomic integrity. The two transcription factors NF-κB and p53 regulate cell fate decisions upon genotoxic stress and therefore play crucial roles in the DNA damage response. To investigate the regulation of NF-κB activity, a mathematical model of coupled ordinary differential equations was developed and analyzed. The model describes DNA damage-induced activation of NF-$&appa;B and quantitatively reproduces multiple experimental data sets. Analyzing the time-resolved regulation of NF-κB revealed regulatory mechanisms of DNA damage-dependent NF-κB signaling and allowed the evaluation of drug targets inhibiting NF-κB activity. Further, the interplay of NF-κB and p53 signaling was investigated by developing a mathematical modeling framework to systematically identify interfaces between the NF-κB and p53 network. NF-κB signaling was perturbed and the resulting changes in single cell dynamics of p53 upon genotoxic stress were captured. By fitting a pool of subpopulation-specific ordinary differential equation models to the single cell data, one of the first quantitative p53 models reproducing the heterogeneous dynamics of p53 was developed. Based on the observed changes in p53 dynamics, the results of the modeling framework indicate that NF-κB signaling interferes with the activation and degradation of p53 as well as the degradation of its inhibitor Mdm2. Taken together, the results in this work give new insights into the regulation of genotoxic NF-κB and p53 signaling and highlight the complexity of their crosstalk.
Download or read book Multidisciplinary Approaches to Theory in Medicine written by and published by Elsevier. This book was released on 2005-12-06 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume will be a collection of chapters from authors with wide experience in their research field. The purpose is to produce a coherent book that reflects the common theme of theory in medical thinking and multidisciplinary research practice. In this context "theory" relates to frameworks of concepts, facts, models etc that help to inform practitioners (clinicians, scientists and engineers) both within their own fields and as they seek to share dialogue with colleagues from other fields. Multidisciplinary Approaches to Theory in Medicine will therefore be integrative across a broad spectrum of fields within medicine. To achieve this the chapters will be associated with others in a number of meaningful ways. Each chapter will share a number of points of contact that will include at least two of the following: Similar biomedical area (e.g., immunity, neuroscience, endocrinology, pathology, oncology, haematology, ...) Similar multidisciplinary theoretical contexts (e.g., modelling, analysis, description, visualization, complex systems, ...) Similar multidisciplinary medical issues and questions (e.g., clinical practice, decision making, informatics, ...) Uniquely explores role of interdisciplinary exchange in the development and expansion of medical theory Timely and insightful essays on the growth and development of medical theories from some of the world's top clinicians and medical researchers, including Werner Arber, Frank Vertosick, and David Weatherall Assembles diverse perspectives on medicine and physiology from biology, statistics, ethics, computer science, philosophy, history Uniquely illuminates the social and historical processes through which theoretical research translates into clinical practice Reveals the growing role of technology, especially computational modelling, in changing the nature of Western medicine
Download or read book Uncertainty in Biology written by Liesbet Geris and published by Springer. This book was released on 2015-10-26 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational modeling allows to reduce, refine and replace animal experimentation as well as to translate findings obtained in these experiments to the human background. However these biomedical problems are inherently complex with a myriad of influencing factors, which strongly complicates the model building and validation process. This book wants to address four main issues related to the building and validation of computational models of biomedical processes: 1. Modeling establishment under uncertainty 2. Model selection and parameter fitting 3. Sensitivity analysis and model adaptation 4. Model predictions under uncertainty In each of the abovementioned areas, the book discusses a number of key-techniques by means of a general theoretical description followed by one or more practical examples. This book is intended for graduate students and researchers active in the field of computational modeling of biomedical processes who seek to acquaint themselves with the different ways in which to study the parameter space of their model as well as its overall behavior.
Download or read book Stochastic Methods for Parameter Estimation and Design of Experiments in Systems Biology written by Andrei Kramer and published by Logos Verlag Berlin GmbH. This book was released on 2016-02-11 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: Markov Chain Monte Carlo (MCMC) methods are sampling based techniques, which use random numbers to approximate deterministic but unknown values. They can be used to obtain expected values, estimate parameters or to simply inspect the properties of a non-standard, high dimensional probability distribution. Bayesian analysis of model parameters provides the mathematical foundation for parameter estimation using such probabilistic sampling. The strengths of these stochastic methods are their robustness and relative simplicity even for nonlinear problems with dozens of parameters as well as a built-in uncertainty analysis. Because Bayesian model analysis necessarily involves the notion of prior knowledge, the estimation of unidentifiable parameters can be regularised (by priors) in a straight forward way. This work draws the focus on typical cases in systems biology: relative data, nonlinear ordinary differential equation models and few data points. It also investigates the consequences of parameter estimation from steady state data; consequences such as performance benefits. In biology the data is almost exclusively relative, the raw measurements (e.g. western blot intensities) are normalised by control experiments or a reference value within a series and require the model to do the same when comparing its output to the data. Several sampling algorithms are compared in terms of effective sampling speed and necessary adaptations to relative and steady state data are explained.
Download or read book Cancer Mortality and Morbidity Patterns in the U S Population written by K.G. Manton and published by Springer Science & Business Media. This book was released on 2008-12-28 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to examine the etiology of cancer in large human populations using mathematical models developed from an inter-disciplinary perspective of the population epidemiological, biodemographic, genetic and physiological basis of the mechanisms of cancer initiation and progression. In addition an investigation of how the basic mechanism of tumor initiation relates to general processes of senescence and to other major chronic diseases (e.g., heart disease and stroke) will be conducted.
Download or read book Cardiac Electrophysiology From Cell to Bedside E Book written by Douglas P. Zipes and published by Elsevier Health Sciences. This book was released on 2017-05-13 with total page 1429 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rapid advancements in cardiac electrophysiology require today’s health care scientists and practitioners to stay up to date with new information both at the bench and at the bedside. The fully revised 7th Edition of Cardiac Electrophysiology: From Cell to Bedside, by Drs. Douglas Zipes, Jose Jalife, and William Stevenson, provides the comprehensive, multidisciplinary coverage you need, including the underlying basic science and the latest clinical advances in the field. An attractive full-color design features color photos, tables, flow charts, ECGs, and more. All chapters have been significantly revised and updated by global leaders in the field, including 19 new chapters covering both basic and clinical topics. New topics include advances in basic science as well as recent clinical technology, such as leadless pacemakers; catheter ablation as a new class I recommendation for atrial fibrillation after failed medical therapy; current cardiac drugs and techniques; and a new video library covering topics that range from basic mapping (for the researcher) to clinical use (implantations). Each chapter is packed with the latest information necessary for optimal basic research as well as patient care, and additional figures, tables, and videos are readily available online. New editor William G. Stevenson, highly regarded in the EP community, brings a fresh perspective to this award-winning text.
