Application Of Logic Synthesis Toward The Inference And Control Of Gene Regulatory Networks
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| Author | : Pey-Chang Kent Lin |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 112 |
| Release | : 2013-10-31 |
| Genre | : Technology & Engineering |
| ISBN | : 146149429X |
This book brings to bear a body of logic synthesis techniques, in order to contribute to the analysis and control of Boolean Networks (BN) for modeling genetic diseases such as cancer. The authors provide several VLSI logic techniques to model the genetic disease behavior as a BN, with powerful implicit enumeration techniques. Coverage also includes techniques from VLSI testing to control a faulty BN, transforming its behavior to a healthy BN, potentially aiding in efforts to find the best candidates for treatment of genetic diseases.
| Author | : Ilya Shmulevich |
| Publisher | : SIAM |
| Total Pages | : 276 |
| Release | : 2010-01-21 |
| Genre | : Mathematics |
| ISBN | : 0898716926 |
The first comprehensive treatment of probabilistic Boolean networks, unifying different strands of current research and addressing emerging issues.
| Author | : Das, Sanjoy |
| Publisher | : IGI Global |
| Total Pages | : 740 |
| Release | : 2009-10-31 |
| Genre | : Computers |
| ISBN | : 1605666866 |
"This book focuses on methods widely used in modeling gene networks including structure discovery, learning, and optimization"--Provided by publisher.
| Author | : Eric H. Davidson |
| Publisher | : Elsevier |
| Total Pages | : 303 |
| Release | : 2010-07-19 |
| Genre | : Science |
| ISBN | : 0080455573 |
Gene regulatory networks are the most complex, extensive control systems found in nature. The interaction between biology and evolution has been the subject of great interest in recent years. The author, Eric Davidson, has been instrumental in elucidating this relationship. He is a world renowned scientist and a major contributor to the field of developmental biology. The Regulatory Genome beautifully explains the control of animal development in terms of structure/function relations of inherited regulatory DNA sequence, and the emergent properties of the gene regulatory networks composed of these sequences. New insights into the mechanisms of body plan evolution are derived from considerations of the consequences of change in developmental gene regulatory networks. Examples of crucial evidence underscore each major concept. The clear writing style explains regulatory causality without requiring a sophisticated background in descriptive developmental biology. This unique text supersedes anything currently available in the market. - The only book in the market that is solely devoted to the genomic regulatory code for animal development - Written at a conceptual level, including many novel synthetic concepts that ultimately simplify understanding - Presents a comprehensive treatment of molecular control elements that determine the function of genes - Provides a comparative treatment of development, based on principles rather than description of developmental processes - Considers the evolutionary processes in terms of the structural properties of gene regulatory networks - Includes 42 full-color descriptive figures and diagrams
| Author | : Ilya Shmulevich |
| Publisher | : Princeton University Press |
| Total Pages | : 314 |
| Release | : 2014-09-08 |
| Genre | : Science |
| ISBN | : 1400865263 |
Genomic signal processing (GSP) can be defined as the analysis, processing, and use of genomic signals to gain biological knowledge, and the translation of that knowledge into systems-based applications that can be used to diagnose and treat genetic diseases. Situated at the crossroads of engineering, biology, mathematics, statistics, and computer science, GSP requires the development of both nonlinear dynamical models that adequately represent genomic regulation, and diagnostic and therapeutic tools based on these models. This book facilitates these developments by providing rigorous mathematical definitions and propositions for the main elements of GSP and by paying attention to the validity of models relative to the data. Ilya Shmulevich and Edward Dougherty cover real-world situations and explain their mathematical modeling in relation to systems biology and systems medicine. Genomic Signal Processing makes a major contribution to computational biology, systems biology, and translational genomics by providing a self-contained explanation of the fundamental mathematical issues facing researchers in four areas: classification, clustering, network modeling, and network intervention.
| Author | : David A. Rosenblueth, |
| Publisher | : Frontiers Media SA |
| Total Pages | : 115 |
| Release | : 2016-11-21 |
| Genre | : |
| ISBN | : 2889450422 |
The complexity of living organisms surpasses our unaided habilities of analysis. Hence, computational and mathematical methods are necessary for increasing our understanding of biological systems. At the same time, there has been a phenomenal recent progress allowing the application of novel formal methods to new domains. This progress has spurred a conspicuous optimism in computational biology. This optimism, in turn, has promoted a rapid increase in collaboration between specialists of biology with specialists of computer science. Through sheer complexity, however, many important biological problems are at present intractable, and it is not clear whether we will ever be able to solve such problems. We are in the process of learning what kind of model and what kind of analysis and synthesis techniques to use for a particular problem. Some existing formalisms have been readily used in biological problems, others have been adapted to biological needs, and still others have been especially developed for biological systems. This Research Topic has examples of cases (1) employing existing methods, (2) adapting methods to biology, and (3) developing new methods. We can also see discrete and Boolean models, and the use of both simulators and model checkers. Synthesis is exemplified by manual and by machine-learning methods. We hope that the articles collected in this Research Topic will stimulate new research.
| Author | : Isabelle S. Peter |
| Publisher | : Academic Press |
| Total Pages | : 461 |
| Release | : 2015-01-21 |
| Genre | : Science |
| ISBN | : 0124047467 |
Genomic Control Process explores the biological phenomena around genomic regulatory systems that control and shape animal development processes, and which determine the nature of evolutionary processes that affect body plan. Unifying and simplifying the descriptions of development and evolution by focusing on the causality in these processes, it provides a comprehensive method of considering genomic control across diverse biological processes. This book is essential for graduate researchers in genomics, systems biology and molecular biology seeking to understand deep biological processes which regulate the structure of animals during development. - Covers a vast area of current biological research to produce a genome oriented regulatory bioscience of animal life - Places gene regulation, embryonic and postembryonic development, and evolution of the body plan in a unified conceptual framework - Provides the conceptual keys to interpret a broad developmental and evolutionary landscape with precise experimental illustrations drawn from contemporary literature - Includes a range of material, from developmental phenomenology to quantitative and logic models, from phylogenetics to the molecular biology of gene regulation, from animal models of all kinds to evidence of every relevant type - Demonstrates the causal power of system-level understanding of genomic control process - Conceptually organizes a constellation of complex and diverse biological phenomena - Investigates fundamental developmental control system logic in diverse circumstances and expresses these in conceptual models - Explores mechanistic evolutionary processes, illuminating the evolutionary consequences of developmental control systems as they are encoded in the genome
| Author | : Sacha Baginsky |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 362 |
| Release | : 2007-06-25 |
| Genre | : Science |
| ISBN | : 376437439X |
This volume aims to provide a timely view of the state-of-the-art in systems biology. The editors take the opportunity to define systems biology as they and the contributing authors see it, and this will lay the groundwork for future studies. The volume is well-suited to both students and researchers interested in the methods of systems biology. Although the focus is on plant systems biology, the proposed material could be suitably applied to any organism.
| Author | : |
| Publisher | : Academic Press |
| Total Pages | : 1571 |
| Release | : 2020-08-24 |
| Genre | : Science |
| ISBN | : 0128160780 |
Technological advances in generated molecular and cell biological data are transforming biomedical research. Sequencing, multi-omics and imaging technologies are likely to have deep impact on the future of medical practice. In parallel to technological developments, methodologies to gather, integrate, visualize and analyze heterogeneous and large-scale data sets are needed to develop new approaches for diagnosis, prognosis and therapy. Systems Medicine: Integrative, Qualitative and Computational Approaches is an innovative, interdisciplinary and integrative approach that extends the concept of systems biology and the unprecedented insights that computational methods and mathematical modeling offer of the interactions and network behavior of complex biological systems, to novel clinically relevant applications for the design of more successful prognostic, diagnostic and therapeutic approaches. This 3 volume work features 132 entries from renowned experts in the fields and covers the tools, methods, algorithms and data analysis workflows used for integrating and analyzing multi-dimensional data routinely generated in clinical settings with the aim of providing medical practitioners with robust clinical decision support systems. Importantly the work delves into the applications of systems medicine in areas such as tumor systems biology, metabolic and cardiovascular diseases as well as immunology and infectious diseases amongst others. This is a fundamental resource for biomedical students and researchers as well as medical practitioners who need to need to adopt advances in computational tools and methods into the clinical practice. Encyclopedic coverage: ‘one-stop’ resource for access to information written by world-leading scholars in the field of Systems Biology and Systems Medicine, with easy cross-referencing of related articles to promote understanding and further research Authoritative: the whole work is authored and edited by recognized experts in the field, with a range of different expertise, ensuring a high quality standard Digitally innovative: Hyperlinked references and further readings, cross-references and diagrams/images will allow readers to easily navigate a wealth of information
| Author | : Gustavo Stolovitzky |
| Publisher | : Wiley-Blackwell |
| Total Pages | : 344 |
| Release | : 2009-05-18 |
| Genre | : Science |
| ISBN | : |
At a microscopic level, organisms are ruled by interacting systems of biomolecules. Historically, scientists painstakingly elucidated chains of molecular events using experiments that reveal individual interactions, although they recognized that members of different pathways frequently interact. In recent years, researchers have built richer, interconnected networks to mathematically summarize their knowledge of these interactions. This systems biology enterprise, largely stimulated by high-throughput tools like microarrays that measure mRNA levels as an indicator of gene expression, is a vital and increasingly important activity in both basic biology and in medicine. A nagging concern, however, is how accurately these networks represent the biology. For complex systems like biological networks, there are practical limits on how well even massive amounts of data can uniquely define the underlying structure and yield useful predictions of measurable events. Indeed, although its advocates call this process "reverse engineering," the topology and the detailed molecular interactions of the "inferred" networks will likely never be known with precision. This volume captures the ongoing process to assess the ability of scientists—and their computer servants—to infer networks from experimental data, by comparing their predictions to "gold-standard" networks whose structure is thought to be known. NOTE: Annals volumes are available for sale as individual books or as a journal. For information on institutional journal subscriptions, please visit www.blackwellpublishing.com/nyas. ACADEMY MEMBERS: Please contact the New York Academy of Sciences directly to place your order (www.nyas.org). Members of the New York Academy of Science receive full-text access to the Annals online and discounts on print volumes. Please visit www.nyas.org/membership/main.asp for more information about becoming a member.
