How can we understand the complexity of genes, RNAs, and proteins and the associated regulatory networks? One approach is to look for recurring types of dynamical behavior. Mathematical models prove to be useful, especially models coming from theories of biochemical reactions such as ordinary differential equation models. Clever, careful experiments test these models and their basis in specific theories. This textbook aims to provide advanced students with the tools and insights needed to carry out studies of signal transduction drawing on modeling, theory, and experimentation. Early chapters summarize the basic building blocks of signaling systems: binding/dissociation, synthesis/destruction, and activation/inactivation. Subsequent chapters introduce various basic circuit devices: amplifiers, stabilizers, pulse generators, switches, stochastic spike generators, and oscillators. All chapters consistently use approaches and concepts from chemical kinetics and nonlinear dynamics, including rate-balance analysis, phase plane analysis, nullclines, linear stability analysis, stable nodes, saddles, unstable nodes, stable and unstable spirals, and bifurcations. This textbook seeks to provide quantitatively inclined biologists and biologically inclined physicists with the tools and insights needed to apply modeling and theory to interesting biological processes. Key Features: Full-color illustration program with diagrams to help illuminate the concepts Enables the reader to apply modeling and theory to the biological processes Further Reading for each chapter High-quality figures available for instructors to download

Topic Editor Prof. Xing is in collaboration with ATCC (https://www.atcc.org/) on testing some of their cell lines in research. All other Topic Editors declare no competing interests with regards to the Research Topic subject.

System Biology encompasses the knowledge from diverse fields such as Molecular Biology, Immunology, Genetics, Computational Biology, Mathematical Biology, etc. not only to address key questions that are not answerable by individual fields alone, but also to help in our understanding of the complexities of biological systems. Whole genome expression studies have provided us the means of studying the expression of thousands of genes under a particular condition and this technique had been widely used to find out the role of key macromolecules that are involved in biological signaling pathways. However, making sense of the underlying complexity is only possible if we interconnect various signaling pathways into human and computer readable network maps. These maps can then be used to classify and study individual components involved in a particular phenomenon. Apart from transcriptomics, several individual gene studies have resulted in adding to our knowledge of key components that are involved in a signaling pathway. It therefore becomes imperative to take into account of these studies also, while constructing our network maps to highlight the interconnectedness of the entire signaling pathways and the role of that particular individual protein in the pathway. This collection of articles will contain a collection of pioneering work done by scientists working in regulatory signaling networks and the use of large scale gene expression and omics data. The distinctive features of this book would be: Act a single source of information to understand the various components of different signaling network (roadmap of biochemical pathways, the nature of a molecule of interest in a particular pathway, etc.), Serve as a platform to highlight the key findings in this highly volatile and evolving field, and Provide answers to various techniques both related to microarray and cell signaling to the readers.

"All living cells continually detect and respond to external signals. This is true of prokaryotes, whether they are living alone or in biofilms, and it is even more manifestly true in multicellular eukaryotes, where communication between cells and coordination of the cells' behavior enables the organism to function as a unified whole. In large multicellular organisms like us humans, cells receive signals from their immediate neighbors through short-range signals like neurotransmitters and cell-surface molecules. They receive signals from more distant neighbors via longer-range diffusible molecules like morphogens, and from still-more distant neighbors by means of hormones that flow through the circulatory system. And they receive signals from the outside world via sense organs. Cells also monitor their own internal status, and there is a great deal of overlap between the cellular components involved in cell-cell communication and internal monitoring"--

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.

This chapter brings mammalian signal transduction to the center of quantitative and integrative sciences. Historically imbedded within human physiology, thanks to proteomics, interactomics, and molecular biology approaches, signaling is now far beyond the “black box” principle. However, despite the large amount of data available, we still have only limited insight into general design principles, and we lack knowledge on how cell type-specific signaling is achieved. Here, we summarize recent efforts in elucidating cell type-specific signaling, and in particular the role of protein abundances, signaling complexes and modules. We further discuss the potential of using synthetic biology approaches to decipher signaling networks. All of this is discussed in light of complementary quantitative mathematical modeling approaches. Signaling, more than any other discipline, needs computational biology to capture the dynamic systems behavior, and to reach its final goal: to be truly predictive for both the physiological and disease perturbed cellular conditions.

Cellular Signal Processing offers a unifying view of cell signaling based on the concept that protein interactions act as sophisticated data processing networks that govern intracellular and extracellular communication. It is intended for use in signal transduction courses for undergraduate and graduate students working in biology, biochemistry, bioinformatics, and pharmacology, as well as medical students. The text is organized by three key topics central to signal transduction: the protein network, its energy supply, and its evolution. It covers all important aspects of cell signaling, ranging from prokaryotic signal transduction to neuronal signaling, and also highlights the clinical aspects of cell signaling in health and disease. This new edition includes expanded coverage of prokaryotes, as well as content on new developments in systems biology, epigenetics, redox signaling, and small, non-coding RNA signaling.