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Author: Sergio Balari
Publisher: Oxford University Press, USA
Published: 2013
Total Pages: 255
ISBN-13: 0199665478
DOWNLOAD EBOOKThis book, written accessibly for both biologists and linguists, argues that language is not as exceptional a human trait as some linguists believe it to be. It is rather, according to the authors, just the human version of a fairly common and conservative organic system, the Central Computational Complex.
Author: A. David Redish
Publisher: MIT Press
Published: 2016-12-09
Total Pages: 425
ISBN-13: 0262035421
DOWNLOAD EBOOKPsychiatrists and neuroscientists discuss the potential of computational approaches to address problems in psychiatry including diagnosis, treatment, and integration with neurobiology. Modern psychiatry is at a crossroads, as it attempts to balance neurological analysis with psychological assessment. Computational neuroscience offers a new lens through which to view such thorny issues as diagnosis, treatment, and integration with neurobiology. In this volume, psychiatrists and theoretical and computational neuroscientists consider the potential of computational approaches to psychiatric issues. This unique collaboration yields surprising results, innovative synergies, and novel open questions. The contributors consider mechanisms of psychiatric disorders, the use of computation and imaging to model psychiatric disorders, ways that computation can inform psychiatric nosology, and specific applications of the computational approach. Contributors Susanne E. Ahmari, Huda Akil, Deanna M. Barch, Matthew Botvinick, Michael Breakspear, Cameron S. Carter, Matthew V. Chafee, Sophie Denève, Daniel Durstewitz, Michael B. First, Shelly B. Flagel, Michael J. Frank, Karl J. Friston, Joshua A. Gordon, Katia M. Harlé, Crane Huang, Quentin J. M. Huys, Peter W. Kalivas, John H. Krystal, Zeb Kurth-Nelson, Angus W. MacDonald III, Tiago V. Maia, Robert C. Malenka, Sanjay J. Mathew, Christoph Mathys, P. Read Montague, Rosalyn Moran, Theoden I. Netoff, Yael Niv, John P. O'Doherty, Wolfgang M. Pauli, Martin P. Paulus, Frederike Petzschner, Daniel S. Pine, A. David Redish, Kerry Ressler, Katharina Schmack, Jordan W. Smoller, Klaas Enno Stephan, Anita Thapar, Heike Tost, Nelson Totah, Jennifer L. Zick
Author: Florian Frommlet
Publisher: Springer
Published: 2016-02-12
Total Pages: 232
ISBN-13: 1447153103
DOWNLOAD EBOOKThis timely text presents a comprehensive guide to genetic association, a new and rapidly expanding field that aims to elucidate how our genetic code (genotypes) influences the traits we possess (phenotypes). The book provides a detailed review of methods of gene mapping used in association with experimental crosses, as well as genome-wide association studies. Emphasis is placed on model selection procedures for analyzing data from large-scale genome scans based on specifically designed modifications of the Bayesian information criterion. Features: presents a thorough introduction to the theoretical background to studies of genetic association (both genetic and statistical); reviews the latest advances in the field; illustrates the properties of methods for mapping quantitative trait loci using computer simulations and the analysis of real data; discusses open challenges; includes an extensive statistical appendix as a reference for those who are not totally familiar with the fundamentals of statistics.
Author: Peter Markstein
Publisher: Imperial College Press
Published: 2008
Total Pages: 355
ISBN-13: 1848162642
DOWNLOAD EBOOKThis proceedings volume contains 29 papers covering many of the latest developments in the fast-growing field of bioinformatics. The contributions span a wide range of topics, including computational genomics and genetics, protein function and computational proteomics, the transcriptome, structural bioinformatics, microarray data analysis, motif identification, biological pathways and systems, and biomedical applications.The papers not only cover theoretical aspects of bioinformatics but also delve into the application of new methods, with input from computation, engineering and biology disciplines. This multidisciplinary approach to bioinformatics gives these proceedings a unique viewpoint of the field.
Author:
Publisher:
Published: 2009
Total Pages: 660
ISBN-13:
DOWNLOAD EBOOKAuthor: Leo Anthony Celi
Publisher: Springer Nature
Published: 2020-07-31
Total Pages: 471
ISBN-13: 3030479943
DOWNLOAD EBOOKThis open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.
Author: Terry Speed
Publisher: Springer
Published: 2007-05-18
Total Pages: 565
ISBN-13: 3540716815
DOWNLOAD EBOOKThis book constitutes the refereed proceedings of the 11th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2007, held in Oakland, CA, USA in April 2007. The 37 revised full papers address all current issues in algorithmic, theoretical, and experimental bioinformatics.
Author: Andres Kriete
Publisher: Academic Press
Published: 2013-11-26
Total Pages: 549
ISBN-13: 0124059384
DOWNLOAD EBOOKThis comprehensively revised second edition of Computational Systems Biology discusses the experimental and theoretical foundations of the function of biological systems at the molecular, cellular or organismal level over temporal and spatial scales, as systems biology advances to provide clinical solutions to complex medical problems. In particular the work focuses on the engineering of biological systems and network modeling. - Logical information flow aids understanding of basic building blocks of life through disease phenotypes - Evolved principles gives insight into underlying organizational principles of biological organizations, and systems processes, governing functions such as adaptation or response patterns - Coverage of technical tools and systems helps researchers to understand and resolve specific systems biology problems using advanced computation - Multi-scale modeling on disparate scales aids researchers understanding of dependencies and constraints of spatio-temporal relationships fundamental to biological organization and function.
Author: Matteo Colombo
Publisher: Cambridge University Press
Published: 2023-11-29
Total Pages: 90
ISBN-13: 1009192833
DOWNLOAD EBOOKThe Computational Theory of Mind says that the mind is a computing system. It has a long history going back to the idea that thought is a kind of computation. Its modern incarnation relies on analogies with contemporary computing technology and the use of computational models. It comes in many versions, some more plausible than others. This Element supports the theory primarily by its contribution to solving the mind-body problem, its ability to explain mental phenomena, and the success of computational modelling and artificial intelligence. To be turned into an adequate theory, it needs to be made compatible with the tractability of cognition, the situatedness and dynamical aspects of the mind, the way the brain works, intentionality, and consciousness.
Author: Ashok Samal
Publisher: CRC Press
Published: 2020-10-21
Total Pages: 347
ISBN-13: 1351709992
DOWNLOAD EBOOKDomesticated crops are the result of artificial selection for particular phenotypes or, in some cases, natural selection for an adaptive trait. Plant traits can be identified through image-based plant phenotyping, a process that was, until recently, strenous and time-consuming. Intelligent Image Analysis for Plant Phenotyping reviews information on time-saving techniques, using computer vision and imaging technologies. These methodologies provide an automated, non-invasive, and scalable mechanism by which to define and collect plant phenotypes. Beautifully illustrated, with numerous color images, the book focuses on phenotypes measured from individual plants under controlled experimental conditions, which are widely available in high-throughput systems. Features: Presents methodologies for image processing, including data-driven and machine learning techniques for plant phenotyping. Features information on advanced techniques for extracting phenotypes through images and image sequences captured in a variety of modalities. Includes real-world scientific problems, including predicting yield by modeling interactions between plant data and environmental information. Discusses the challenge of translating images into biologically informative quantitative phenotypes. A practical resource for students, researchers, and practitioners, this book is invaluable for those working in the emerging fields at the intersection of computer vision and plant sciences.
