Biology In The Grid

How grids paved the way for our biological understanding of organisms As one of the most visual sciences, biology has an aesthetic dimension that lends force and persuasion to scientific arguments: how things are arranged on a page, how texts are interspersed with images, and how images are composed reflect deep-seated beliefs about how life exists on Earth. Biology in the Grid traces how our current understanding of life and genetics emerged from the pervasive nineteenth- and twentieth-century graphic form of the grid, which allowed disparate pieces of information to form what media theorist Vilém Flusser called “technical images.” Phillip Thurtle explains how the grid came to dominate biology in the twentieth century, transforming biologists’ beliefs about how organisms were constructed. He demonstrates how this shift in our understanding of biological grids enabled new philosophies in endeavors such as advertising, entertainment, and even political theory. The implications of the arguments in Biology in the Grid are profound, touching on matters as fundamental as desire, our understanding of our bodies, and our view of how society is composed. Moreover, Thurtle’s beautifully written, tightly focused arguments allow readers to apply his claims to new disciplines and systems. Bristling with insight and potential, Biology in the Grid ultimately suggests that such a grid-organized understanding of natural life inevitably has social and political dimensions, with society recognized as being made of interchangeable, regulated parts rather than as an organic whole.

The only single, up-to-date source for Grid issues in bioinformatics and biology Bioinformatics is fast emerging as an important discipline for academic research and industrial applications, creating a need for the use of Grid computing techniques for large-scale distributed applications. This book successfully presents Grid algorithms and their real-world applications, provides details on modern and ongoing research, and explores software frameworks that integrate bioinformatics and computational biology. Additional coverage includes: * Bio-ontology and data mining * Data visualization * DNA assembly, clustering, and mapping * Molecular evolution and phylogeny * Gene expression and micro-arrays * Molecular modeling and simulation * Sequence search and alignment * Protein structure prediction * Grid infrastructure, middleware, and tools for bio data Grid Computing for Bioinformatics and Computational Biology is an indispensable resource for professionals in several research and development communities including bioinformatics, computational biology, Grid computing, data mining, and more. It also serves as an ideal textbook for undergraduate- and graduate-level courses in bioinformatics and Grid computing.

The book constitutes the refereed proceedings of the International Workshop on Distributed, High-Performance and Grid Computing in Computational Biology, GCCB 2006, held in Eilat, Israel in January 2007 in conjunction with the 5th European Conference on Computational Biology, ECCB 2006. The 13 revised full papers presented were carefully reviewed and selected from many high quality submissions.

The distributed computing infrastructure known as ‘the Grid’ has undoubtedly been one of the most successful science-oriented large- scale IT projects of the past 20 years. It is now a fully operational international entity, encompassing several hundred computing sites on all continents and giving access to hundreds of thousands of CPU (central processing unit) cores and hundreds of petabytes of storage, all connected by robust national and international scientific networks. It has evolved to become the main computational platform many scientific communities. This book presents lectures from the Enrico Fermi International School of Physics summer school Grid and Cloud computing: Concepts and Practical Applications, held in Varenna, Italy, in July 2014. The school aimed to cover the conceptual and practical aspects of both the Grid and Cloud computing. The proceedings included here are divided into eight chapters, with chapters 1, 2, 3 and 8 covering general applications of Grid and Cloud computing in various scientific fields, while chapters 4, 5, 6 and 7 discuss specific technical areas of Grid and Cloud structures. The book will be of interest to all those whose work involves the use of the Grid or Cloud computing.

Unter "Grid Computing" versteht man die gleichzeitige Nutzung vieler Computer in einem Netzwerk für die Lösung eines einzelnen Problems. Grundsätzliche Aspekte und anwendungsbezogene Details zu diesem Gebiet finden Sie in diesem Band. - Grid Computing ist ein viel versprechender Trend, denn man kann damit (1) vorhandene Computer-Ressourcen kosteneffizient nutzen, (2) Probleme lösen, für die enorme Rechenleistungen erforderlich sind, und (3) Synergieeffekte erzielen, auch im globalen Maßstab - Ansatz ist in Forschung und Industrie (IBM, Sun, HP und andere) zunehmend populär (aktuelles Beispiel: Genomforschung) - Buch deckt Motivationen zur Einführung von Grids ebenso ab wie technologische Grundlagen und ausgewählte Beispiele für moderne Anwendungen

Fred Van Dyke’s new textbook, Conservation Biology: Foundations, Concepts, Applications, 2nd Edition, represents a major new text for anyone interested in conservation. Drawing on his vast experience, Van Dyke’s organizational clarity and readable style make this book an invaluable resource for students in conservation around the globe. Presenting key information and well-selected examples, this student-friendly volume carefully integrates the science of conservation biology with its implications for ethics, law, policy and economics.

Technology is taking us to a world where myriads of heavily networked devices interact with the physical world in multiple ways, and at many levels, from the globalInternetdowntomicroandnanodevices. Manyofthesedevicesarehighly mobile and autonomous and must adapt to the surrounding environment in a totally unsupervised way. A fundamental research challenge is the design of robust decentralized c- puting systemsthat arecapableofoperating in changing environmentsandwith noisy input, and yet exhibit the desired behavior and response time, under c- straints such as energy consumption, size, and processing power. These systems should be able to adapt and learn how to react to unforeseen scenarios as well as to display properties comparable to social entities. The observation of nature has brought us many great and unforeseen concepts. Biological systems are able to handle many of these challenges with an elegance and e?ciency far beyond currenthumanartifacts. Basedonthisobservation,bio-inspiredapproacheshave been proposed as a means of handling the complexity of such systems. The goal is to obtain methods to engineer technical systems, which are of a stability and e?ciency comparable to those found in biological entities. This Special Issue on Biological and Biologically-inspired Communication contains the best papers from the Second International Conference on Bio- Inspired Models of Network, Information, and Computing Systems (BIONET- ICS 2007). The BIONETICS conference aims to bring together researchers and scientistsfromseveraldisciplines incomputerscienceandengineeringwhereb- inspired methods are investigated, as well as from bioinformatics, to deepen the information exchange and collaboration among the di?erent communities.

This book constitutes the refereed proceedings of the First International Conference, AlCoB 2014, held in July 2014 in Tarragona, Spain. The 20 revised full papers were carefully reviewed and selected from 39 submissions. The scope of AlCoB includes topics of either theoretical or applied interest, namely: exact sequence analysis, approximate sequence analysis, pairwise sequence alignment, multiple sequence alignment, sequence assembly, genome rearrangement, regulatory motif finding, phylogeny reconstruction, phylogeny comparison, structure prediction, proteomics: molecular pathways, interaction networks, transcriptomics: splicing variants, isoform inference and quantification, differential analysis, next-generation sequencing: population genomics, metagenomics, metatranscriptomics, microbiome analysis, systems biology.