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Computational Phenotypes by Sergio Balari,Guillermo Lorenzo,Guillermo Lorenzo González Pdf
This is a book about language as a species-typical trait of humans. It argues that language is not so exceptional after all, as according to the authors it is just the human version of a rather common and conservative organic system that they refer to as the Central Computational Complex.
Phenotypes and Genotypes by Florian Frommlet,Małgorzata Bogdan,David Ramsey Pdf
This 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 : A. David Redish,Joshua A. Gordon Publisher : MIT Press Page : 425 pages File Size : 44,9 Mb Release : 2016-12-09 Category : Science ISBN : 9780262035422
Computational Psychiatry by A. David Redish,Joshua A. Gordon Pdf
Psychiatrists 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
The Computational Theory of Mind by Matteo Colombo,Gualtiero Piccinini Pdf
The 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.
Research in Computational Molecular Biology by Terry Speed,Haiyan Huang Pdf
This 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.
Intelligent Image Analysis for Plant Phenotyping by Ashok Samal,Sruti Das Choudhury Pdf
Domesticated 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.
Beyond the DSM by Steven C. Hayes,Stefan G. Hofmann Pdf
As a mental health clinician, you know that every client is unique, and a client’s symptoms are the result of a complex combination of psychological, environmental, genetic, and neural factors. However, the de facto DSM model poses considerable constraints on how you can treat clients—often resulting in a one-size-fits-all diagnosis. This important volume challenges the assumptions and approach made by the DSM, and provides a vision and plan for an evidence-based, process-based approach to individualized care. With contributions from renowned experts in the field—including Steven C. Hayes, Stefan G. Hofmann, Joseph Ciarrochi, Matthew McKay, Uma Vaidyanathan, Sarah Morris, David Sommers, J. Scott Fraser, and many more—this groundbreaking book will show you a new way to recognize the complexity of human suffering and human prosperity. You’ll find solid tips for treating a wide variety of psychological issues in a more flexible way. And, finally, you’ll come away with a greater understanding of the “processes of change,” and how to build a solid foundation for an alternative to syndromal diagnosis. The future of mental health treatment is process-based. Whether you’re a clinician, researcher, student, instructor, or other professional working in the mental health field, this breakthrough volume offers everything you need to understand process-based treatment and create a more customized and effective approach to treating clients.
Computational Complexity and Statistical Physics by Allon Percus,Gabriel Istrate,Cristopher Moore Pdf
Computer science and physics have been closely linked since the birth of modern computing. In recent years, an interdisciplinary area has blossomed at the junction of these fields, connecting insights from statistical physics with basic computational challenges. Researchers have successfully applied techniques from the study of phase transitions to analyze NP-complete problems such as satisfiability and graph coloring. This is leading to a new understanding of the structure of these problems, and of how algorithms perform on them. Computational Complexity and Statistical Physics will serve as a standard reference and pedagogical aid to statistical physics methods in computer science, with a particular focus on phase transitions in combinatorial problems. Addressed to a broad range of readers, the book includes substantial background material along with current research by leading computer scientists, mathematicians, and physicists. It will prepare students and researchers from all of these fields to contribute to this exciting area.
Phenotyping; From Plant, to Data, to Impact and Highlights of the The International Plant Phenotyping Symposium - IPPS 2018 by Trevor Garnett,Carolyn J. Lawrence-Dill,Tony Pridmore,Michelle Watt,Cyril Pommier,Roland Pieruschka,Kioumars Ghamkhar Pdf
National Research Council,Division on Earth and Life Studies,Division on Engineering and Physical Sciences,Committee on the Potential Impact of High-End Computing on Illustrative Fields of Science and Engineering
Author : National Research Council,Division on Earth and Life Studies,Division on Engineering and Physical Sciences,Committee on the Potential Impact of High-End Computing on Illustrative Fields of Science and Engineering Publisher : National Academies Press Page : 158 pages File Size : 47,8 Mb Release : 2008-10-28 Category : Technology & Engineering ISBN : 9780309134439
The Potential Impact of High-End Capability Computing on Four Illustrative Fields of Science and Engineering by National Research Council,Division on Earth and Life Studies,Division on Engineering and Physical Sciences,Committee on the Potential Impact of High-End Computing on Illustrative Fields of Science and Engineering Pdf
Many federal funding requests for more advanced computer resources assume implicitly that greater computing power creates opportunities for advancement in science and engineering. This has often been a good assumption. Given stringent pressures on the federal budget, the White House Office of Management and Budget (OMB) and Office of Science and Technology Policy (OSTP) are seeking an improved approach to the formulation and review of requests from the agencies for new computing funds. This book examines, for four illustrative fields of science and engineering, how one can start with an understanding of their major challenges and discern how progress against those challenges depends on high-end capability computing (HECC). The four fields covered are: atmospheric science astrophysics chemical separations evolutionary biology This book finds that all four of these fields are critically dependent on HECC, but in different ways. The book characterizes the components that combine to enable new advances in computational science and engineering and identifies aspects that apply to multiple fields.
Current Challenges in Cardiovascular Molecular Diagnostics by Matteo Vatta,Valeria Novelli,Luisa Mestroni,Jeffrey A. Towbin,Carlo Napolitano,Guia Guffanti Pdf
The field of cardiovascular genetics has tremendously benefited from the recent application of massive parallel sequencing technology also referred to as next generation sequencing (NGS). However, along with the discovery of additional genes associated with human cardiac diseases, the analysis of large dataset of genetic information uncovered a much more complex and variegated landscape, which often departs from the comfort zone of the monogenic Mendelian diseases image that clinical molecular geneticists have been well acquainted with for many decades. It is now clear that, in addition to highly penetrant genetic variants, which in isolation are able to recapitulate the full clinical presentation when expressed in animal models, we are now aware that a small but significant fraction of subjects presenting with cardiac muscle diseases such as cardiomyopathies or primary arrhythmias such as long QT syndrome (LQTS), may harbor at least two deleterious variants in the same gene (compound heterozygous) or in different gene (double heterozygous). Although the clinical presentation in subjects with more than one deleterious variant appears to be more severe and with an earlier disease onset, it somehow changes the viewpoint of clinical molecular geneticists whose aim is to identify all possible genetic contributors to a human condition. In this light, the employment in clinical diagnostics of the NGS technology, allowing the simultaneous interrogation of a DNA target spanning from large panel of genes up to the entire genome, will definitely aid at uncovering all such contributors, which will have to be tested functionally to confirm their role in human cardiac conditions. The uncovering of all clinically relevant deleterious changes associated with a cardiovascular disease would probably increase our understanding of the clinical variability commonly occurring among affected family relatives, and potentially provide with unexpected therapeutic targets for the treatment of symptoms related to the presence of “accessory” deleterious genetic variants other than the key molecular culprit. The objective of this Research Topic is to explore the current challenges presenting to the cardiovascular genetics providers, such as clinical geneticists, genetic counselors, clinical molecular geneticists and molecular pathologists involved in the diagnosis, counseling, testing and interpretation of genetic tests results for the comprehensive management of patients affected by cardiovascular genetic disorders.
Applying Computational Intelligence by Arthur Kordon Pdf
In theory, there is no difference between theory and practice. But, in practice, there is. Jan L. A. van de Snepscheut The ?ow of academic ideas in the area of computational intelligence has penetrated industry with tremendous speed and persistence. Thousands of applications have proved the practical potential of fuzzy logic, neural networks, evolutionary com- tation, swarm intelligence, and intelligent agents even before their theoretical foundation is completely understood. And the popularity is rising. Some software vendors have pronounced the new machine learning gold rush to “Transfer Data into Gold”. New buzzwords like “data mining”, “genetic algorithms”, and “swarm optimization” have enriched the top executives’ vocabulary to make them look more “visionary” for the 21st century. The phrase “fuzzy math” became political jargon after being used by US President George W. Bush in one of the election debates in the campaign in 2000. Even process operators are discussing the perf- mance of neural networks with the same passion as the performance of the Dallas Cowboys. However, for most of the engineers and scientists introducing computational intelligence technologies into practice, looking at the growing number of new approaches, and understanding their theoretical principles and potential for value creation becomes a more and more dif?cult task.
