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Author: Marco Pellegrini
Publisher: Frontiers Media SA
ISBN: 288963650X
Category :
Languages : en
Pages : 270
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Book Description
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.
Author: Marco Pellegrini
Publisher: Frontiers Media SA
ISBN: 288963650X
Category :
Languages : en
Pages : 270
Get Book Here
Book Description
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.
Author: N. P. O. Green
Publisher: Cambridge University Press
ISBN: 9780521639231
Category : Juvenile Nonfiction
Languages : en
Pages : 992
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Book Description
Cambridge Low Price Editions are reprints of internationally respected books from Cambridge University Press. The text has been completely revised and updated to provide comprehensive coverage of all the major biology syllabuses at Advanced level. It is also suitable for first-year students in higher education. It contains: clearly written up-to-date information appropriate to the new Advanced level biology syllabuses, new material covering microbiology and biotechnology, the applications of genetics, and human health and disease, a variety of questions throughout the text, carefully selected and clearly presented practical investigations in many of the units, appendices providing basic information and techniques relating to the relevant areas of the physical sciences and mathematics (e.g.biological chemistry and statistics)
Author: Alla Borisyuk
Publisher: Springer Science & Business Media
ISBN: 9783540238584
Category : Mathematics
Languages : en
Pages : 184
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Book Description
This volume introduces some basic theories on computational neuroscience. Chapter 1 is a brief introduction to neurons, tailored to the subsequent chapters. Chapter 2 is a self-contained introduction to dynamical systems and bifurcation theory, oriented towards neuronal dynamics. The theory is illustrated with a model of Parkinson's disease. Chapter 3 reviews the theory of coupled neural oscillators observed throughout the nervous systems at all levels; it describes how oscillations arise, what pattern they take, and how they depend on excitory or inhibitory synaptic connections. Chapter 4 specializes to one particular neuronal system, namely, the auditory system. It includes a self-contained introduction, from the anatomy and physiology of the inner ear to the neuronal network that connects the hair cells to the cortex, and describes various models of subsystems.
Author: Todd D. Little
Publisher: Oxford University Press, USA
ISBN: 019937015X
Category : Psychology
Languages : en
Pages : 536
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Book Description
The Oxford Handbook of Quantitative Methods in Psychology provides an accessible and comprehensive review of the current state-of-the-science and a one-stop source for best practices in a quantitative methods across the social, behavioral, and educational sciences.
Author: Das, Sanjoy
Publisher: IGI Global
ISBN: 1605666866
Category : Computers
Languages : en
Pages : 740
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Book Description
"This book focuses on methods widely used in modeling gene networks including structure discovery, learning, and optimization"--Provided by publisher.
Author: Mark R. T. Dale
Publisher: Cambridge University Press
ISBN: 1108491847
Category : Language Arts & Disciplines
Languages : en
Pages : 233
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Book Description
Displays the broad range of quantitative approaches to analysing ecological networks, providing clear examples and guidance for researchers.
Author: Eberhard O. Voit
Publisher: Garland Science
ISBN: 1136215107
Category : Computers
Languages : en
Pages : 465
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Book Description
A First Course in Systems Biology is a textbook designed for advanced undergraduate and graduate students. Its main focus is the development of computational models and their applications to diverse biological systems. Because the biological sciences have become so complex that no individual can acquire complete knowledge in any given area of specialization, the education of future systems biologists must instead develop a student's ability to retrieve, reformat, merge, and interpret complex biological information. This book provides the reader with the background and mastery of methods to execute standard systems biology tasks, understand the modern literature, and launch into specialized courses or projects that address biological questions using theoretical and computational means. The format is a combination of instructional text and references to primary literature, complemented by sets of small-scale exercises that enable hands-on experience, and larger-scale, often open-ended questions for further reflection.
Author: Marco Scutari
Publisher: CRC Press
ISBN: 1000410382
Category : Computers
Languages : en
Pages : 275
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Book Description
Explains the material step-by-step starting from meaningful examples Steps detailed with R code in the spirit of reproducible research Real world data analyses from a Science paper reproduced and explained in detail Examples span a variety of fields across social and life sciences Overview of available software in and outside R
Author: Basilio de Braganca Pereira
Publisher: CRC Press
ISBN: 0429775555
Category : Business & Economics
Languages : en
Pages : 234
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Book Description
Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks starting from the basics and increasingly demanding more effort from readers, who can learn the theory and its applications in statistical methods with concrete Python code examples. It presents a wide range of widely used statistical methodologies, applied in several research areas with Python code examples, which are available online. It is suitable for scientists and developers as well as graduate students. Key Features: Discusses applications in several research areas Covers a wide range of widely used statistical methodologies Includes Python code examples Gives numerous neural network models This book covers fundamental concepts on Neural Networks including Multivariate Statistics Neural Networks, Regression Neural Network Models, Survival Analysis Networks, Time Series Forecasting Networks, Control Chart Networks, and Statistical Inference Results. This book is suitable for both teaching and research. It introduces neural networks and is a guide for outsiders of academia working in data mining and artificial intelligence (AI). This book brings together data analysis from statistics to computer science using neural networks.
Author: Peter Fleming
Publisher: CSIRO PUBLISHING
ISBN: 1486300413
Category : Science
Languages : en
Pages : 441
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Book Description
Camera trapping in wildlife management and research is a growing global phenomenon. The technology is advancing very quickly, providing unique opportunities for collecting new biological knowledge. In order for fellow camera trap researchers and managers to share their knowledge and experience, the First International Camera Trapping Colloquium in Wildlife Management and Research was held in Sydney, Australia. Camera Trapping brings together papers from a selection of the presentations at the colloquium and provides a benchmark of the international developments and uses of camera traps for monitoring wildlife for research and management. Four major themes are presented: case studies demonstrating camera trapping for monitoring; the constraints and pitfalls of camera technologies; design standards and protocols for camera trapping surveys; and the identification, management and analyses of the myriad images that derive from camera trapping studies. The final chapter provides future directions for research using camera traps. Remarkable photographs are included, showing interesting, enlightening and entertaining images of animals 'doing their thing'.
