Systems Biology And Computational Proteomics

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.

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 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 book reflects more than three decades of research on Cellular Automata (CA), and nearly a decade of work on the application of CA to model biological strings, which forms the foundation of 'A New Kind of Computational Biology' pioneered by the start-up, CARLBio. After a brief introduction on Cellular Automata (CA) theory and functional biology, it reports on the modeling of basic biological strings with CA, starting with the basic nucleotides leading to codon and anti-codon CA models. It derives a more involved CA model of DNA, RNA, the entire translation process for amino acid formation and the evolution of protein to its unique structure and function. In subsequent chapters the interaction of Proteins with other bio-molecules is also modeled. The only prior knowledge assumed necessary is an undergraduate knowledge of computer programming and biology. The book adopts a hands-on, “do-it-yourself” approach to enable readers to apply the method provided to derive the CA rules and comprehend how these are related to the physical ‘rules’ observed in biology. In a single framework, the authors have presented two branches of science – Computation and Biology. Instead of rigorous molecular dynamics modeling, which the authors describe as a Bottoms-Up model, or relying on the Top-Down new age Artificial Intelligence (AI) and Machine Language (ML) that depends on extensive availability of quality data, this book takes the best from both the Top-Down and Bottoms-up approaches and establishes how the behavior of complex molecules is represented in CA. The CA rules are derived from the basic knowledge of molecular interaction and construction observed in biological world but mapped to a few subset of known results to derive and predict results. This book is useful for students, researchers and industry practitioners who want to explore modeling and simulation of the physical world complex systems from a different perspective. It raises the inevitable the question – ‘Are life and the universe nothing but a collection of continuous systems processing information’.

Systems Biology is concerned with the quantitative study of complex biosystems at the molecular, cellular, tissue, and systems scales. Its focus is on the function of the system as a whole, rather than on individual parts. This exciting new arena applies mathematical modeling and engineering methods to the study of biological systems. This book is the first of its kind to focus on the newly emerging field of systems biology with an emphasis on computational approaches. The work covers new concepts, methods for information storage, mining and knowledge extraction, reverse engineering of gene and metabolic networks, as well as modelling and simulation of multi-cellular systems. Central themes include strategies for predicting biological properties and methods for elucidating structure-function relationships.

This book explains omics at the most basic level, including how this new concept can be properly utilized in molecular and systems biology research. Most reviews and books on this topic have mainly focused on the technicalities and complexity of each omics’ platform, impeding readers to wholly understand its fundamentals and applications. This book tackles such gap and will be most beneficial to novice in this area, university students and even researchers. Basic workflow and practical guidance in each omics are also described, such that scientists can properly design their experimentation effectively. Furthermore, how each omics platform has been conducted in our institute (INBIOSIS) is also detailed, a comprehensive example on this topic to further enhance readers’ understanding. The contributors of each chapter have utilized the platforms in various manner within their own research and beyond. The contributors have also been interactively integrated and combined these different omics approaches in their research, being able to systematically write each chapter with the conscious knowledge of other inter-relating topics of omics. The potential readers and audience of this book can come from undergraduate and postgraduate students who wish to extend their comprehension in the topics of molecular biology and big data analysis using omics platforms. Furthermore, researchers and scientists whom may have expertise in basic molecular biology can extend their experimentation using the omics technologies and workflow outlined in this book, benefiting their research in the long run.