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Model identification and data analysis
This book is about constructing models from experimental data. It covers a range of topics, from statistical data prediction to Kalman filtering, from black-box model identification to parameter estimation, from spectral analysis to predictive control.Written for graduate students, this textbook offers an approach that has proven successful throughout the many years during which its author has taught these topics at his University.The book:Contains accessible methods explained step-by-step in simple termsOffers an essential tool useful in a variety of fields, especially engineering, statistics, and mathematicsIncludes an overview on random variables and stationary processes, as well as an introduction to discrete time models and matrix analysisIncorporates historical commentaries to put into perspective the developments that have brought the discipline to its current stateProvides many examples and solved problems to complement the presentation and facilitate comprehension of the techniques presented
eBook
Collecting experiments : making Big Data biology
Databases have revolutionized nearly every aspect of our lives. Information of all sorts is being collected on a massive scale, from Google to Facebook and well beyond. But as the amount of information in databases explodes, we are forced to reassess our ideas about what knowledge is, how it is produced, to whom it belongs, and who can be credited for producing it. Every scientist working today draws on databases to produce scientific knowledge. Databases have become more common than microscopes, voltmeters, and test tubes, and the increasing amount of data has led to major changes in research practices and profound reflections on the proper professional roles of data producers, collectors, curators, and analysts. Collecting Experiments traces the development and use of data collections, especially in the experimental life sciences, from the early twentieth century to the present. It shows that the current revolution is best understood as the coming together of two older ways of knowing--collecting and experimenting, the museum and the laboratory. Ultimately, Bruno J. Strasser argues that by serving as knowledge repositories, as well as indispensable tools for producing new knowledge, these databases function as digital museums for the twenty-first century.
Book
Models of Seizures and Epilepsy
An understanding of mechanisms underlying seizure disorders depends critically on the insights provided by model systems. In particular with the development of cellular, molecular, and genetic investigative tools, there has been an explosion of basic epilepsy research. Models of Seizures and Epilepsy brings together, for the first time in 30 years, an overview of the most widely-used models of seizures and epilepsy. Chapters cover a broad range of experimental approaches (from in vitro to whole animal preparations), a variety of epileptiform phenomenology (including burst discharges and seizures), and suggestions for model characterization and validation, such as electrographic, morphologic, pharmacologic, and behavioral features. Experts in the field provide not only technical reviews of these models but also conceptual critiques - commenting on the strengths and limitations of these models, their relationship to clinical phenomenology, and their value in developing a better understanding and treatments. Models of Seizures and Epilepsy is a valuable, practical reference for investigators who are searching for the most appropriate laboratory models for addressing key questions in the field. It also provides an important background for physicians, fellows, and students, offering insight into the potential for advances in epilepsy research. · The first comprehensive description of animal models of epilepsy since the early 1970's· Comprehensive analysis of \"What the models model\" to guide the selection of each model, and what specific questions it will answer· Elegant examples of the use of novel technologies that can be applied in experimental epilepsy research· World expert opinions on the clinical relevance of each model
eBook
Vitamin E and Its Molecular Effects in Experimental Models of Neurodegenerative Diseases
With the advancement of in vivo studies and clinical trials, the pathogenesis of neurodegenerative diseases has been better understood. However, gaps still need to be better elucidated, which justifies the publication of reviews that explore the mechanisms related to the development of these diseases. Studies show that vitamin E supplementation can protect neurons from the damage caused by oxidative stress, with a positive impact on the prevention and progression of neurodegenerative diseases. Thus, this review aims to summarize the scientific evidence of the effects of vitamin E supplementation on neuroprotection and on neurodegeneration markers in experimental models. A search for studies published between 2000 and 2023 was carried out in the PubMed, Web of Science, Virtual Health Library (BVS), and Embase databases, in which the effects of vitamin E in experimental models of neurodegeneration were investigated. A total of 5669 potentially eligible studies were identified. After excluding the duplicates, 5373 remained, of which 5253 were excluded after checking the titles, 90 articles after reading the abstracts, and 11 after fully reviewing the manuscripts, leaving 19 publications to be included in this review. Experiments with in vivo models of neurodegenerative diseases demonstrated that vitamin E supplementation significantly improved memory, cognition, learning, motor function, and brain markers associated with neuroregeneration and neuroprotection. Vitamin E supplementation reduced beta-amyloid (Aβ) deposition and toxicity in experimental models of Alzheimer’s disease. In addition, it decreased tau-protein hyperphosphorylation and increased superoxide dismutase and brain-derived neurotrophic factor (BDNF) levels in rodents, which seems to indicate the potential use of vitamin E in preventing and delaying the progress of degenerative lesions in the central nervous system.
Journal Article
Observed brain dynamics
The biomedical sciences have recently undergone revolutionary change, due to the ability to digitize and store large data sets. In neuroscience, the data sources include measurements of neural activity measured using electrode arrays, EEG and MEG, brain imaging data from PET, fMRI, and optical imaging methods. Analysis, visualization, and management of these time series data sets is a growing field of research that has become increasingly important both for experimentalists and theorists interested in brain function. The first part of the book contains a set of chapters which provide non-technical conceptual background to the subject. Salient features include the adoption of an active perspective of the nervous system, an emphasis on function, and a brief survey of different theoretical accounts in neuroscience. The second part is the longest in the book, and contains a refresher course in mathematics and statistics leading up to time series analysis techniques. The third part contains applications of data analysis techniques to the range of data sources indicated above, and the fourth part contains special topics.
eBook
Exploring Animal Social Networks
Social network analysis is used widely in the social sciences to study interactions among people, groups, and organizations, yet until now there has been no book that shows behavioral biologists how to apply it to their work on animal populations.Exploring Animal Social Networksprovides a practical guide for researchers, undergraduates, and graduate students in ecology, evolutionary biology, animal behavior, and zoology.
Existing methods for studying animal social structure focus either on one animal and its interactions or on the average properties of a whole population. This book enables researchers to probe animal social structure at all levels, from the individual to the population. No prior knowledge of network theory is assumed. The authors give a step-by-step introduction to the different procedures and offer ideas for designing studies, collecting data, and interpreting results. They examine some of today's most sophisticated statistical tools for social network analysis and show how they can be used to study social interactions in animals, including cetaceans, ungulates, primates, insects, and fish. Drawing from an array of techniques, the authors explore how network structures influence individual behavior and how this in turn influences, and is influenced by, behavior at the population level. Throughout, the authors use two software packages--UCINET and NETDRAW--to illustrate how these powerful analytical tools can be applied to different animal social organizations.
eBook
Animal models of autism spectrum disorder: Insights into genetic, structural and environmental models
Autism spectrum disorder (ASD) is a group of human neurodevelopmental disorders with significant global prevalence. Deficits in social communication and interaction and repetitive, stereotyped patterns of behaviour characterise ASD. The aetiology of ASD is unclear, but several genetic and environmental risk factors, either alone or in combination, are implicated in its development. To date, the underlying pathogenic mechanisms of ASD remain incompletely understood due to its heterogeneity. To better understand the pathogenesis of ASD, various animal models have been developed. The use of animals in ASD research allows the exploration of the biological substrates of social behaviour, cognition, and reward sensitivity, which are key components of ASD symptoms. This review outlines the commonly employed animal models in ASD research and explores their applications and the associated challenges.
Journal Article
The geographic spread of infectious diseases
The 1918-19 influenza epidemic killed more than fifty million people worldwide. The SARS epidemic of 2002-3, by comparison, killed fewer than a thousand. The success in containing the spread of SARS was due largely to the rapid global response of public health authorities, which was aided by insights resulting from mathematical models. Models enabled authorities to better understand how the disease spread and to assess the relative effectiveness of different control strategies. In this book, Lisa Sattenspiel and Alun Lloyd provide a comprehensive introduction to mathematical models in epidemiology and show how they can be used to predict and control the geographic spread of major infectious diseases.
Key concepts in infectious disease modeling are explained, readers are guided from simple mathematical models to more complex ones, and the strengths and weaknesses of these models are explored. The book highlights the breadth of techniques available to modelers today, such as population-based and individual-based models, and covers specific applications as well. Sattenspiel and Lloyd examine the powerful mathematical models that health authorities have developed to understand the spatial distribution and geographic spread of influenza, measles, foot-and-mouth disease, and SARS. Analytic methods geographers use to study human infectious diseases and the dynamics of epidemics are also discussed. A must-read for students, researchers, and practitioners, no other book provides such an accessible introduction to this exciting and fast-evolving field.
eBook