Model Systems In Biology
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Model Systems In Biology
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Author : Georg Striedter
language : en
Publisher: MIT Press
Release Date : 2022-08-02
Model Systems In Biology written by Georg Striedter and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-02 with Science categories.
How biomedical research using various animal species and in vitro cellular systems has resulted in both major successes and translational failure. In Model Systems in Biology, comparative neurobiologist Georg Striedter examines how biomedical researchers have used animal species and in vitro cellular systems to understand and develop treatments for human diseases ranging from cancer and polio to Alzheimer’s disease and schizophrenia. Although there have been some major successes, much of this “translational” research on model systems has failed to generalize to humans. Striedter explores the history of such research, focusing on the models used and considering the question of model selection from a variety of perspectives—the philosophical, the historical, and that of practicing biologists. Striedter reviews some philosophical concepts and ethical issues, including concerns over animal suffering and the compromises that result. He traces the history of the most widely used animal and in vitro models, describing how they compete with one another in a changing ecosystem of models. He examines how therapies for bacterial and viral infections, cancer, cardiovascular diseases, and neurological disorders have been developed using animal and cell culture models—and how research into these diseases has both taken advantage of and been hindered by model system differences. Finally, Striedter argues for a “big tent” biology, in which a diverse set of models and research strategies can coexist productively.
Marine Organisms As Model Systems In Biology And Medicine
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Author : Malgorzata Kloc
language : en
Publisher: Springer
Release Date : 2018-08-06
Marine Organisms As Model Systems In Biology And Medicine written by Malgorzata Kloc and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-06 with Science categories.
This book highlights the potential advantages of using marine invertebrates like tunicates, echinoderms, sponges and cephalopods as models in both biological and medical research. Bioactive compounds found in marine organisms possess antibacterial, antifungal, anti-diabetic and anti-inflammatory properties, and can affect the immune and nervous systems. Despite substantial research on the medicinal attributes of various marine invertebrates, they are still very much underrepresented in scientific literature: the majority of cell, developmental and evolutionary scientific journals only publish research conducted on a few well-known model systems like Drosophila melanogaster or Xenopus laevis. Addressing that gap, this book introduces readers to new model organisms like starfish or nemertera. By showing their benefits with regard to regeneration, stem cell research and Evo-Devo, the authors provide a cross-sectional view encompassing various disciplines of biological research. As such, this book will not only appeal to scientists currently working on marine organisms, but will also inspire future generations to pursue research of their own.
Model Systems In Biology
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Author : Georg F. Striedter
language : en
Publisher:
Release Date : 2022
Model Systems In Biology written by Georg F. Striedter and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Animal experimentation categories.
"Instead of arguing for a specific animal model, Striedter will review the history and philosophy of animal models in biomedical research, examining their various advantages and limitations"--
Model Organisms In Drug Discovery
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Author : Pamela M. Carroll
language : en
Publisher: John Wiley & Sons
Release Date : 2004-04-21
Model Organisms In Drug Discovery written by Pamela M. Carroll and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-04-21 with Science categories.
Fruit flies are "little people with wings" goes the saying in the scientific community, ever since the completion of the Human Genome Project and its revelations about the similarity amongst the genomes of different organisms. It is humbling that most signalling pathways which "define" humans are conserved in Drosophila, the common fruit fly. Feed a fruit fly caffeine and it has trouble falling asleep; feed it antihistamines and it cannot stay awake. A C. elegans worm placed on the antidepressant flouxetine has increased serotonin levels in its tiny brain. Yeast treated with chemotherapeutics stop their cell division. Removal of a single gene from a mouse or zebrafish can cause the animals to develop Alzheimer’s disease or heart disease. These organisms are utilized as surrogates to investigate the function and design of complex human biological systems. Advances in bioinformatics, proteomics, automation technologies and their application to model organism systems now occur on an industrial scale. The integration of model systems into the drug discovery process, the speed of the tools, and the in vivo validation data that these models can provide, will clearly help definition of disease biology and high-quality target validation. Enhanced target selection will lead to the more efficacious and less toxic therapeutic compounds of the future. Leading experts in the field provide detailed accounts of model organism research that have impacted on specific therapeutic areas and they examine state-of-the-art applications of model systems, describing real life applications and their possible impact in the future. This book will be of interest to geneticists, bioinformaticians, pharmacologists, molecular biologists and people working in the pharmaceutical industry, particularly genomics.
Emerging Model Systems In Developmental Biology
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Author :
language : en
Publisher: Academic Press
Release Date : 2022-03-23
Emerging Model Systems In Developmental Biology written by and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-23 with Science categories.
An ever-growing roster of model organisms is a hallmark of 21st century Developmental Biology. Emerging model organisms are well suited to asking some fascinating and important questions that cannot be addressed using established model systems. And new methods are increasingly facilitating the adoption of new research organisms in laboratories. This volume is written by some of the scientists who have played pivotal roles in developing new models or in significantly advancing tools in emerging systems. Presents some of the most interesting additions to the core set of model organisms Contains contributions from people who have developed new model systems or advanced tools Includes personal stories about how and why model systems were developed
Systems Biology
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Author : Andreas Kremling
language : en
Publisher: CRC Press
Release Date : 2013-11-12
Systems Biology written by Andreas Kremling and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-12 with Mathematics categories.
Drawing on the latest research in the field, Systems Biology: Mathematical Modeling and Model Analysis presents many methods for modeling and analyzing biological systems, in particular cellular systems. It shows how to use predictive mathematical models to acquire and analyze knowledge about cellular systems. It also explores how the models are sy
Stochastic Modelling For Systems Biology Third Edition
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Author : Darren J. Wilkinson
language : en
Publisher: CRC Press
Release Date : 2018-12-07
Stochastic Modelling For Systems Biology Third Edition written by Darren J. Wilkinson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-07 with Mathematics categories.
Since the first edition of Stochastic Modelling for Systems Biology, there have been many interesting developments in the use of "likelihood-free" methods of Bayesian inference for complex stochastic models. Having been thoroughly updated to reflect this, this third edition covers everything necessary for a good appreciation of stochastic kinetic modelling of biological networks in the systems biology context. New methods and applications are included in the book, and the use of R for practical illustration of the algorithms has been greatly extended. There is a brand new chapter on spatially extended systems, and the statistical inference chapter has also been extended with new methods, including approximate Bayesian computation (ABC). Stochastic Modelling for Systems Biology, Third Edition is now supplemented by an additional software library, written in Scala, described in a new appendix to the book. New in the Third Edition New chapter on spatially extended systems, covering the spatial Gillespie algorithm for reaction diffusion master equation models in 1- and 2-d, along with fast approximations based on the spatial chemical Langevin equation Significantly expanded chapter on inference for stochastic kinetic models from data, covering ABC, including ABC-SMC Updated R package, including code relating to all of the new material New R package for parsing SBML models into simulatable stochastic Petri net models New open-source software library, written in Scala, replicating most of the functionality of the R packages in a fast, compiled, strongly typed, functional language Keeping with the spirit of earlier editions, all of the new theory is presented in a very informal and intuitive manner, keeping the text as accessible as possible to the widest possible readership. An effective introduction to the area of stochastic modelling in computational systems biology, this new edition adds additional detail and computational methods that will provide a stronger foundation for the development of more advanced courses in stochastic biological modelling.
Model Based Hypothesis Testing In Biomedicine
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Author : Rikard Johansson
language : en
Publisher: Linköping University Electronic Press
Release Date : 2017-10-03
Model Based Hypothesis Testing In Biomedicine written by Rikard Johansson and has been published by Linköping University Electronic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-03 with categories.
The utilization of mathematical tools within biology and medicine has traditionally been less widespread compared to other hard sciences, such as physics and chemistry. However, an increased need for tools such as data processing, bioinformatics, statistics, and mathematical modeling, have emerged due to advancements during the last decades. These advancements are partly due to the development of high-throughput experimental procedures and techniques, which produce ever increasing amounts of data. For all aspects of biology and medicine, these data reveal a high level of inter-connectivity between components, which operate on many levels of control, and with multiple feedbacks both between and within each level of control. However, the availability of these large-scale data is not synonymous to a detailed mechanistic understanding of the underlying system. Rather, a mechanistic understanding is gained first when we construct a hypothesis, and test its predictions experimentally. Identifying interesting predictions that are quantitative in nature, generally requires mathematical modeling. This, in turn, requires that the studied system can be formulated into a mathematical model, such as a series of ordinary differential equations, where different hypotheses can be expressed as precise mathematical expressions that influence the output of the model. Within specific sub-domains of biology, the utilization of mathematical models have had a long tradition, such as the modeling done on electrophysiology by Hodgkin and Huxley in the 1950s. However, it is only in recent years, with the arrival of the field known as systems biology that mathematical modeling has become more commonplace. The somewhat slow adaptation of mathematical modeling in biology is partly due to historical differences in training and terminology, as well as in a lack of awareness of showcases illustrating how modeling can make a difference, or even be required, for a correct analysis of the experimental data. In this work, I provide such showcases by demonstrating the universality and applicability of mathematical modeling and hypothesis testing in three disparate biological systems. In Paper II, we demonstrate how mathematical modeling is necessary for the correct interpretation and analysis of dominant negative inhibition data in insulin signaling in primary human adipocytes. In Paper III, we use modeling to determine transport rates across the nuclear membrane in yeast cells, and we show how this technique is superior to traditional curve-fitting methods. We also demonstrate the issue of population heterogeneity and the need to account for individual differences between cells and the population at large. In Paper IV, we use mathematical modeling to reject three hypotheses concerning the phenomenon of facilitation in pyramidal nerve cells in rats and mice. We also show how one surviving hypothesis can explain all data and adequately describe independent validation data. Finally, in Paper I, we develop a method for model selection and discrimination using parametric bootstrapping and the combination of several different empirical distributions of traditional statistical tests. We show how the empirical log-likelihood ratio test is the best combination of two tests and how this can be used, not only for model selection, but also for model discrimination. In conclusion, mathematical modeling is a valuable tool for analyzing data and testing biological hypotheses, regardless of the underlying biological system. Further development of modeling methods and applications are therefore important since these will in all likelihood play a crucial role in all future aspects of biology and medicine, especially in dealing with the burden of increasing amounts of data that is made available with new experimental techniques. Användandet av matematiska verktyg har inom biologi och medicin traditionellt sett varit mindre utbredd jämfört med andra ämnen inom naturvetenskapen, såsom fysik och kemi. Ett ökat behov av verktyg som databehandling, bioinformatik, statistik och matematisk modellering har trätt fram tack vare framsteg under de senaste decennierna. Dessa framsteg är delvis ett resultat av utvecklingen av storskaliga datainsamlingstekniker. Inom alla områden av biologi och medicin så har dessa data avslöjat en hög nivå av interkonnektivitet mellan komponenter, verksamma på många kontrollnivåer och med flera återkopplingar både mellan och inom varje nivå av kontroll. Tillgång till storskaliga data är emellertid inte synonymt med en detaljerad mekanistisk förståelse för det underliggande systemet. Snarare uppnås en mekanisk förståelse först när vi bygger en hypotes vars prediktioner vi kan testa experimentellt. Att identifiera intressanta prediktioner som är av kvantitativ natur, kräver generellt sett matematisk modellering. Detta kräver i sin tur att det studerade systemet kan formuleras till en matematisk modell, såsom en serie ordinära differentialekvationer, där olika hypoteser kan uttryckas som precisa matematiska uttryck som påverkar modellens output. Inom vissa delområden av biologin har utnyttjandet av matematiska modeller haft en lång tradition, såsom den modellering gjord inom elektrofysiologi av Hodgkin och Huxley på 1950?talet. Det är emellertid just på senare år, med ankomsten av fältet systembiologi, som matematisk modellering har blivit ett vanligt inslag. Den något långsamma adapteringen av matematisk modellering inom biologi är bl.a. grundad i historiska skillnader i träning och terminologi, samt brist på medvetenhet om exempel som illustrerar hur modellering kan göra skillnad och faktiskt ofta är ett krav för en korrekt analys av experimentella data. I detta arbete tillhandahåller jag sådana exempel och demonstrerar den matematiska modelleringens och hypotestestningens allmängiltighet och tillämpbarhet i tre olika biologiska system. I Arbete II visar vi hur matematisk modellering är nödvändig för en korrekt tolkning och analys av dominant-negativ-inhiberingsdata vid insulinsignalering i primära humana adipocyter. I Arbete III använder vi modellering för att bestämma transporthastigheter över cellkärnmembranet i jästceller, och vi visar hur denna teknik är överlägsen traditionella kurvpassningsmetoder. Vi demonstrerar också frågan om populationsheterogenitet och behovet av att ta hänsyn till individuella skillnader mellan celler och befolkningen som helhet. I Arbete IV använder vi matematisk modellering för att förkasta tre hypoteser om hur fenomenet facilitering uppstår i pyramidala nervceller hos råttor och möss. Vi visar också hur en överlevande hypotes kan beskriva all data, inklusive oberoende valideringsdata. Slutligen utvecklar vi i Arbete I en metod för modellselektion och modelldiskriminering med hjälp av parametrisk ”bootstrapping” samt kombinationen av olika empiriska fördelningar av traditionella statistiska tester. Vi visar hur det empiriska ”log-likelihood-ratio-testet” är den bästa kombinationen av två tester och hur testet är applicerbart, inte bara för modellselektion, utan också för modelldiskriminering. Sammanfattningsvis är matematisk modellering ett värdefullt verktyg för att analysera data och testa biologiska hypoteser, oavsett underliggande biologiskt system. Vidare utveckling av modelleringsmetoder och tillämpningar är därför viktigt eftersom dessa sannolikt kommer att spela en avgörande roll i framtiden för biologi och medicin, särskilt när det gäller att hantera belastningen från ökande datamängder som blir tillgänglig med nya experimentella tekniker.
Modeling Dynamic Biological Systems
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Author : Bruce Hannon
language : en
Publisher: Springer
Release Date : 2014-07-05
Modeling Dynamic Biological Systems written by Bruce Hannon and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-05 with Science categories.
Many biologists and ecologists have developed models that find widespread use in theoretical investigations and in applications to organism behavior, disease control, population and metapopulation theory, ecosystem dynamics, and environmental management. This book captures and extends the process of model development by concentrating on the dynamic aspects of these processes and by providing the tools such that virtually anyone with basic knowledge in the Life Sciences can develop meaningful dynamic models. Examples of the systems modeled in the book range from models of cell development, the beating heart, the growth and spread of insects, spatial competition and extinction, to the spread and control of epidemics, including the conditions for the development of chaos. Key features: - easy-to-learn and easy-to-use software - examples from many subdisciplines of biology, covering models of cells, organisms, populations, and metapopulations - no prior computer or programming experience required Key benefits: - learn how to develop modeling skills and system thinking on your own rather than use models developed by others - be able to easily run models under alternative assumptions and investigate the implications of these assumptions for the dynamics of the biological system being modeled - develop skills to assess the dynamics of biological systems
Dynamic Systems Biology Modeling And Simulation
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Author : Joseph DiStefano III
language : en
Publisher: Academic Press
Release Date : 2015-01-10
Dynamic Systems Biology Modeling And Simulation written by Joseph DiStefano III and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-10 with Science categories.
Dynamic Systems Biology Modeling and Simuation consolidates and unifies classical and contemporary multiscale methodologies for mathematical modeling and computer simulation of dynamic biological systems – from molecular/cellular, organ-system, on up to population levels. The book pedagogy is developed as a well-annotated, systematic tutorial – with clearly spelled-out and unified nomenclature – derived from the author’s own modeling efforts, publications and teaching over half a century. Ambiguities in some concepts and tools are clarified and others are rendered more accessible and practical. The latter include novel qualitative theory and methodologies for recognizing dynamical signatures in data using structural (multicompartmental and network) models and graph theory; and analyzing structural and measurement (data) models for quantification feasibility. The level is basic-to-intermediate, with much emphasis on biomodeling from real biodata, for use in real applications. Introductory coverage of core mathematical concepts such as linear and nonlinear differential and difference equations, Laplace transforms, linear algebra, probability, statistics and stochastics topics The pertinent biology, biochemistry, biophysics or pharmacology for modeling are provided, to support understanding the amalgam of “math modeling” with life sciences Strong emphasis on quantifying as well as building and analyzing biomodels: includes methodology and computational tools for parameter identifiability and sensitivity analysis; parameter estimation from real data; model distinguishability and simplification; and practical bioexperiment design and optimization Companion website provides solutions and program code for examples and exercises using Matlab, Simulink, VisSim, SimBiology, SAAMII, AMIGO, Copasi and SBML-coded models A full set of PowerPoint slides are available from the author for teaching from his textbook. He uses them to teach a 10 week quarter upper division course at UCLA, which meets twice a week, so there are 20 lectures. They can easily be augmented or stretched for a 15 week semester course Importantly, the slides are editable, so they can be readily adapted to a lecturer’s personal style and course content needs. The lectures are based on excerpts from 12 of the first 13 chapters of DSBMS. They are designed to highlight the key course material, as a study guide and structure for students following the full text content The complete PowerPoint slide package (~25 MB) can be obtained by instructors (or prospective instructors) by emailing the author directly, at: [email protected]