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This book constitutes the thoroughly refereed post-proceedings of two joint RECOMB 2006 satellite events: the Second Annual Workshop on Systems Biology, RSB 2006, and the First Biennial Workshop on Computational Proteomics, RCP 2006, held in San Diego, CA, USA in December 2006. The papers cover various aspects of systems biology and explore the use of computational mass spectrometry in various proteomic applications.
Proteomics and Systems Biology, Volume 127 in the Advances in Protein Chemistry and Structural Biology series, outlines current proteomic methodologies and discuss the challenges in future applications of systems biology in a number of biomedical/bioscience subjects. In last few decades, advances in genomics, proteomics, metabolomics, glycomics, venomics, etc., have produced vast large-scale datasets that need to be analyzed with a single main objective of understanding biological systems as a whole. Such understanding will allow us to predict and characterize the dynamic properties of biological systems. Integrates experimental and computational methods for understanding biological systems as a whole Contains timely chapters written by well-renowned authorities in their field Includes well supported content that is accompanied by a number of high-quality illustrations, figures and tables, hence it targets a wide audience of specialists, researchers and students
This book constitutes the thoroughly refereed post-proceedings of two joint RECOMB 2006 satellite events: the Second Annual Workshop on Systems Biology, RSB 2006, and the First Biennial Workshop on Computational Proteomics, RCP 2006, held in San Diego, CA, USA in December 2006. The papers cover various aspects of systems biology and explore the use of computational mass spectrometry in various proteomic applications.
The LNCS journal Transactions on Computational Systems Biology is devoted to inter- and multidisciplinary research in the fields of computer science and life sciences and supports a paradigmatic shift in the techniques from computer and information science to cope with the new challenges arising from the systems oriented point of view of biological phenomena. This first volume of the Transactions on Computational Systems Biology is made up of papers by members of the journal's Editorial Board to provide a representative and smart start-up to the new journal.
This detailed book highlights the diverse techniques and applications of proteomics in an accessible, informative, and concise manner. The collection features sample preparation from distinct extraction, quantification, enrichment, modification, as well as interactome methodology for the in-depth exploration of biological systems, and the application of proteomics to clinical, infectious disease, and agricultural practices. Moreover, cutting-edge bioinformatics tools, encompassing machine learning and data integration strategies, are explored, as are techniques expanding beyond proteomics into the realm of metabolomics. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting known pitfalls. Comprehensive and practical, Proteomics in Systems Biology: Methods and Protocols emphasizes the importance of proteomics and demonstrates a plethora of approaches for investigating diverse biological entities from a systems perspective.
The rapidly developing field of systems biology is influencing many aspects of biological research and is expected to transform biomedicine. Some emerging offshoots and specialized branches in systems biology are receiving particular attention and are becoming highly active areas of research. This collection of invited reviews describes some of the latest cutting-edge experimental and computational advances in these emerging sub-fields of systems biology. In particular, this collection focuses on the study of mammalian embryonic stem cells; new technologies involving mass-spectrometry proteomics; single cell measurements; methods for modeling complex stochastic systems; network-based classification algorithms; and the revolutionary emerging field of systems pharmacology.
Biological and biomedical sciences are becoming more interdisciplinary, and scientists of the future need inte rdisciplinary training instead of the conventional disciplinary training. Just as Sean Eddy (2005) wiselypointed out that sending monolingual diplomats to the United Nations maynot enhance international collaborations, combining strictly disciplinary scientists trained in either mathematics, computational science or molecular biology will not create a productive inte rdisciplinary team ready to solve interdisciplinary problems. Molecular biology is an interdiscip linary science back in its heyday, and founders of molecular biology were ofte n interdisciplinary scientists. Indeed, Francis Crick considered himself as “a mixture of crystallographer, biophysicist, biochemist, and geneticist” (Crick, 1965). Because it was too cumbersome to explain to people that he was such a mixture, the term “molecular biologist” came handy. To get the crystallographer, biophysicist, biochemist, and geneticist within hi mself to collaborate with each other probably worked better than a team with a crystallographer, a biophysicist, a biochemist and a geneticist who maynot even be interested in each other’s problems.
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.
The LNCS journal Transactions on Computational Systems Biology is devoted to inter- and multidisciplinary research in the fields of computer science and life sciences and supports a paradigmatic shift in the techniques from computer and information science to cope with the new challenges arising from the systems-oriented point of view of biological phenomena. This, the third Transactions on Computational Systems Biology volume, edited by Emanuela Merelli, Pedro Pablo Gonzalez and Andrea Omicini, is devoted to considerably extended versions of selected papers presented at the International Workshop on Network Tools and Applications in Biology (NETTAB 2004), held at the University of Camerino, in Camerino, Italy, in September 2004. Dedicated especially to models and metaphors from biology to bioinformatics tools, the 10 papers selected for the special issue cover a wide range of bioinformatics research such as data visualisation, protein/RNA structure prediction, motif finding, modelling and simulation of protein interaction, genetic linkage analysis, and notations and models for systems biology.