This book presents recent methods for Systems Genetics (SG) data analysis, applying them to a suite of simulated SG benchmark datasets. Each of the chapter authors received the same datasets to evaluate the performance of their method to better understand which algorithms are most useful for obtaining reliable models from SG datasets. The knowledge gained from this benchmarking study will ultimately allow these algorithms to be used with confidence for SG studies e.g. of complex human diseases or food crop improvement. The book is primarily intended for researchers with a background in the life sciences, not for computer scientists or statisticians.
Systems biology is a critical emerging field that quantifies and annotates the complexity of biological systems in order to construct algorithmic models to predict outcomes from component input. Applications in medicine are revolutionizing our understanding of biological processes and systems. Systems Biomedicine is organized around foundations, computational modeling, network biology, and integrative biology, with the extension of examples from human biology and pharmacology, to focus on the applications of systems approaches to medical problems. An integrative approach to the underlying genomic, proteomic, and computational biology principles provides researchers with guidance in the use of qualitative systems and hypothesis generators. To reflect the highly interdisciplinary nature of the field, careful detail has been extended to ensure explanations of complex mathematical and biological principles are clear with minimum technical jargon. - Organized to reflect the important distinguishing characteristics of systems strategies in experimental biology and medicine - Provides precise and comprehensive measurement tools for constructing a model of the system and tools for defining complexity as an experimental dependent variable - Includes a thorough discussion of the applications of quantitative principles to biomedical problems
The systems biology of microbial infections aims at describing and analysing the confrontation of the host with bacterial and fungal pathogens. It intends to understand and to model the interaction of the host, in particular the immune system of humans or animals, with components of pathogens. This comprises experimental studies that provide spatio-temporal data from monitoring the response of host and pathogenic cells to perturbations or when interacting with each other, as well as the integrative analysis of genome-wide data from both the host and the pathogen. In perspective, the host-pathogen interaction should be described by a combination of spatio-temporal models with interacting molecular networks of the host and the pathogen. The aim is to unravel the main mechanisms of pathogenicity, to identify diagnostic biomarkers and potential drug targets, and to explore novel strategies for personalized therapy by computer simulations. Some microorganisms are part of the normal microbial flora, existing either in a mutualistic or commensal relationship with the host. Microorganisms become pathogenic if they posses certain physiological characteristics and virulence determinants as well as capabilities for immune evasion. Despite the different pathogenesis of infections, there are several common traits: (1) Before infection, pathogens must be able to overcome (epithelial) barriers. The infection starts by adhesion and colonization and is followed by entering of the pathogen into the host through the mucosa or (injured) skin. (2) Next, infection arises if the pathogen multiplies and overgrows the normal microbial flora, either at the place of entrance or in deeper tissue layers or organs. (3) After the growth phase, the pathogen damages the host’s cells, tissues and organs by producing toxins or destructive enzymes. Thus, systems biology of microbial infection comprises all levels of the pathogen and the host’s immune system. The investigation may start with the pathogen, its adhesion and colonization at the host, its interaction with host cell types e.g. epithelia cells, dendritic cells, macrophages, neutrophils, natural killer cells, etc. Because infection diseases are mainly found in patients with a weakened immune system, e.g. reduced activities of immune effector cells or defects in the epithelial barriers, systems biology of infection can also start with modelling of the immune defence including innate and adaptive immunity. Systems biological studies comprise both experimental and theoretical approaches. The experimental studies may be dedicated to reveal the relevance of certain genes or proteins in the above mentioned processes on the side of the pathogen and/or the host by applying functional and biochemical analyses based on knock-out mutants and knock- down experiments. At the theoretical, i.e. mathematical and computational, side systems biology of microbial infection comprises: (1) modelling of molecular mechanisms of bacterial or fungal infections, (2) modelling of non-protective and protective immune defences against microbial pathogens to generate information for possible immune therapy approaches, (3) modelling of infection dynamics and identification of biomarkers for diagnosis and for individualized therapy, (4) identifying essential virulence determinants and thereby predicting potential drug targets.
A First Course in Systems Biology is an introduction for advanced undergraduate and graduate students to the growing field of systems biology. Its main focus is the development of computational models and their applications to diverse biological systems. The book begins with the fundamentals of modeling, then reviews features of the molecular inventories that bring biological systems to life and discusses case studies that represent some of the frontiers in systems biology and synthetic biology. In this way, it provides the reader with a comprehensive background and access to methods for executing standard systems biology tasks, understanding the modern literature, and launching into specialized courses or projects that address biological questions using theoretical and computational means. New topics in this edition include: default modules for model design, limit cycles and chaos, parameter estimation in Excel, model representations of gene regulation through transcription factors, derivation of the Michaelis-Menten rate law from the original conceptual model, different types of inhibition, hysteresis, a model of differentiation, system adaptation to persistent signals, nonlinear nullclines, PBPK models, and elementary modes. The format is a combination of instructional text and references to primary literature, complemented by sets of small-scale exercises that enable hands-on experience, and large-scale, often open-ended questions for further reflection.
Bacterial Molecular Networks provides authoritative descriptions of various experimental and computational methods that enable the characterization and analysis of molecular interaction networks.
1 Kevin Moses It is now 25 years since the study of the development of the compound eye in Drosophila really began with a classic paper (Ready et al. 1976). In 1864, August Weismann published a monograph on the development of Diptera and included some beautiful drawings of the developing imaginal discs (Weismann 1864). One of these is the first description of the third instar eye disc in which Weismann drew a vertical line separating a posterior domain that included a regular pattern of clustered cells from an anterior domain without such a pattern. Weismann suggested that these clusters were the precursors of the adult ommatidia and that the line marks the anterior edge of the eye. In his first suggestion he was absolutely correct - in his second he was wrong. The vertical line shown was not the anterior edge of the eye, but the anterior edge of a moving wave of patterning and cell type specification that 112 years later (1976) Ready, Hansen and Benzer would name the "morphogenetic furrow". While it is too late to hear from August Weismann, it is a particular pleasure to be able to include a chapter in this Volume from the first author of that 1976 paper: Don Ready! These past 25 years have seen an astonishing explosion in the study of the fly eye (see Fig.
The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by 'Data Mining' address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining.
The availability of molecular imaging and measurement systems enables today's biologists to swiftly monitor thousands of genes involved in a host of diseases, a critical factor in specialized drug development. Systems Biology and Bioinformatics: A Computational Approach provides students with a comprehensive collection of the computational methods
This book explores Systems Biology as the understanding of biological network behaviors, and in particular their dynamic aspects, which requires the utilization of mathematical modeling tightly linked to experiment. A variety of approaches are discussed here: the identification and validation of networks, the creation of appropriate datasets, the development of tools for data acquisition and software development, and the use of modeling and simulation software in close concert with experiment.
Immuno Systems Biology aims to study the immune system in the more integrated manner on how cells and molecules participate at different system levels to the immune function. Through this book Kumar Selvarajoo introduces to physicists, chemists, computer scientists, biologists and immunologists the idea of an integrated approach to the understanding of mammalian immune system. Geared towards a researcher with limited immunological and computational analytical experience, the book provides a broad overview to the subject and some instruction in basic computational, theoretical and experimental approaches. The book links complex immunological processes with computational analysis and emphasizes the importance of immunology to the mammalian system.
