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Biological and biomedical studies have entered a new era over the past two decades thanks to the wide use of mathematical models and computational approaches. A booming of computational biology, which sheerly was a theoretician’s fantasy twenty years ago, has become a reality. Obsession with computational biology and theoretical approaches is evidenced in articles hailing the arrival of what are va- ously called quantitative biology, bioinformatics, theoretical biology, and systems biology. New technologies and data resources in genetics, such as the International HapMap project, enable large-scale studies, such as genome-wide association st- ies, which could potentially identify most common genetic variants as well as rare variants of the human DNA that may alter individual’s susceptibility to disease and the response to medical treatment. Meanwhile the multi-electrode recording from behaving animals makes it feasible to control the animal mental activity, which could potentially lead to the development of useful brain–machine interfaces. - bracing the sheer volume of genetic, genomic, and other type of data, an essential approach is, ?rst of all, to avoid drowning the true signal in the data. It has been witnessed that theoretical approach to biology has emerged as a powerful and st- ulating research paradigm in biological studies, which in turn leads to a new - search paradigm in mathematics, physics, and computer science and moves forward with the interplays among experimental studies and outcomes, simulation studies, and theoretical investigations.
This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.
This book explains the state-of-the-art algorithms used to simulate biological dynamics. Each technique is theoretically introduced and applied to a set of modeling cases. Starting from basic simulation algorithms, the book also introduces more advanced techniques that support delays, diffusion in space, or that are based on hybrid simulation strategies. This is a valuable self-contained resource for graduate students and practitioners in computer science, biology and bioinformatics. An appendix covers the mathematical background, and the authors include further reading sections in each chapter.
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.
This volume addresses the latest state-of-the-art systems biology-oriented approaches that--driven by big data and bioinformatics--are utilized by Computational Systems Biology, an interdisciplinary field that bridges experimental tools with computational tools to tackle complex questions at the frontiers of knowledge in medicine and biotechnology. The chapters in this book are organized into six parts: systems biology of the genome, epigenome, and redox proteome; metabolic networks; aging and longevity; systems biology of diseases; spatiotemporal patterns of rhythms, morphogenesis, and complex dynamics; and genome scale metabolic modeling in biotechnology. In every chapter, readers will find varied methodological approaches applied at different levels, from molecular, cellular, organ to organisms, genome to phenome, and health and disease. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics; criteria utilized for applying specific methodologies; lists of the necessary materials, reagents, software, databases, algorithms, mathematical models, and dedicated analytical procedures; step-by-step, readily reproducible laboratory, bioinformatics, and computational protocols all delivered in didactic and clear style and abundantly illustrated with express case studies and tutorials; and tips on troubleshooting and advice for achieving reproducibility while avoiding mistakes and misinterpretations. The overarching goal driving this volume is to excite the expert and stimulate the newcomer to the field of Computational Systems Biology. Cutting-edge and authoritative, Computational Systems Biology in Medicine and Biotechnology: Methods and Protocols is a valuable resource for pre- and post-graduate students in medicine and biotechnology, and in diverse areas ranging from microbiology to cellular and organismal biology, as well as computational and experimental biologists, and researchers interested in utilizing comprehensive systems biology oriented methods.
This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.
Transcription regulation is a complex process that can be considered and investigated from different perspectives. Traditionally and due to technical reasons (including the evolution of our understanding of the underlying processes) the main focus of the research was made on the regulation of expression through transcription factors (TFs), the proteins directly binding to DNA. On the other hand, intensive research is going on in the field of chromatin structure, remodeling and its involvement in the regulation. Whatever direction we select, we can speak about several levels of regulation. For instance, concentrating on TFs, we should consider multiple regulatory layers, starting with signaling pathways and ending up with the TF binding sites in the promoters and other regulatory regions. However, it is obvious that the TF regulation, also including the upstream processes, represents a modest portion of all processes leading to gene expression. For more comprehensive description of the gene regulation, we need a systematic and holistic view, which brings us to the importance of systems biology approaches. Advances in methodology, especially in high-throughput methods, result in an ever-growing mass of data, which in many cases is still waiting for appropriate consideration. Moreover, the accumulation of data is going faster than the development of algorithms for their systematic evaluation. Data and methods integration is indispensable for the acquiring a systematic as well as a systemic view. In addition to the huge amount of molecular or genetic components of a biological system, the even larger number of their interactions constitutes the enormous complexity of processes occurring in a living cell (organ, organism). In systems biology, these interactions are represented by networks. Transcriptional or, more generally, gene regulatory networks are being generated from experimental ChIPseq data, by reverse engineering from transcriptomics data, or from computational predictions of transcription factor (TF) – target gene relations. While transcriptional networks are now available for many biological systems, mathematical models to simulate their dynamic behavior have been successfully developed for metabolic and, to some extent, for signaling networks, but relatively rarely for gene regulatory networks. Systems biology approaches provide new perspectives that raise new questions. Some of them address methodological problems, others arise from the newly obtained understanding of the data. These open questions and problems are also a subject of this Research Topic.
This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.
This textbook has been conceptualized to provide a detailed description of the various aspects of Systems and Synthetic Biology, keeping the requirements of M.Sc. and Ph.D. students in mind. Also, it is hoped that this book will mentor young scientists who are willing to contribute to this area but do not know from where to begin. The book has been divided into two sections. The first section will deal with systems biology – in terms of the foundational understanding, highlighting issues in biological complexity, methods of analysis and various aspects of modelling. The second section deals with the engineering concepts, design strategies of the biological systems ranging from simple DNA/RNA fragments, switches and oscillators, molecular pathways to a complete synthetic cell will be described. Finally, the book will offer expert opinions in legal, safety, security and social issues to present a well-balanced information both for students and scientists.
Computing is revolutionizing the practice of biology. This book, which assumes no prior computing experience, provides students with the tools to write their own Python programs and to understand fundamental concepts in computational biology and bioinformatics. Each major part of the book begins with a compelling biological question, followed by the algorithmic ideas and programming tools necessary to explore it: the origins of pathogenicity are examined using gene finding, the evolutionary history of sex determination systems is studied using sequence alignment, and the origin of modern humans is addressed using phylogenetic methods. In addition to providing general programming skills, this book explores the design of efficient algorithms, simulation, NP-hardness, and the maximum likelihood method, among other key concepts and methods. Easy-to-read and designed to equip students with the skills to write programs for solving a range of biological problems, the book is accompanied by numerous programming exercises, available at www.cs.hmc.edu/CFB.