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Neuropeptide Analogs, Conjugates, and Fragments

Gene expression --- Technique.

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Epigenetic Gene Expression and Regulation reviews current knowledge on the heritable molecular mechanisms that regulate gene expression, contribute to disease susceptibility, and point to potential treatment in future therapies. The book shows how these heritable mechanisms allow individual cells to establish stable and unique patterns of gene expression that can be passed through cell divisions without DNA mutations, thereby establishing how different heritable patterns of gene regulation control cell differentiation and organogenesis, resulting in a distinct human organism with a variety of differing cellular functions and tissues. The work begins with basic biology, encompasses methods, cellular and tissue organization, topical issues in epigenetic evolution and environmental epigenesis, and lastly clinical disease discovery and treatment. Each highly illustrated chapter is organized to briefly summarize current research, provide appropriate pedagogical guidance, pertinent methods, relevant model organisms, and clinical examples. - Reviews current knowledge on the heritable molecular mechanisms that regulate gene expression, contribute to disease susceptibility, and point to potential treatment in future therapies - Helps readers understand how epigenetic marks are targeted, and to what extent transgenerational epigenetic changes are instilled and possibly passed onto offspring - Chapters are replete with clinical examples to empower the basic biology with translational significance - Offers more than 100 illustrations to distill key concepts and decipher complex science.

Epigenetics. --- Gene expression. --- Genetic regulation.

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Prokaryotic gene expression is not only of theoretical interest but also of highly practical significance. It has implications for other biological problems, such as developmental biology and cancer, brings insights into genetic engineering and expression systems, and has consequences for important aspects of applied research. For example, the molecular basis of bacterial pathogenicity has implications for new antibiotics and in crop development. Prokaryotic Gene; Expression is a major review of the subject, providing up-to-date coverage as well as numerous insights by the prestigious authors. Topics covered include operons; protein recognition of sequence specific DNA- and RNA-binding sites; promoters; sigma factors, and variant tRNA polymerases; repressors and activators;; post-transcriptional control and attenuation; ribonuclease activity, mRNA stability, and translational repression; prokaryotic DNA topology, topoisomerases, and gene expression; regulatory networks, regulatory cascades and signal transduction; phosphotransfer reactions; switch systems, transcriptional and translational modulation, methylation, and recombination mechanisms; pathogenicity, toxin regulation and virulence determinants; sporulation and genetic regulation of antibiotic production;; origins of regulatory molecules, selective pressures and evolution of prokaryotic regulatory mechanisms systems. Over 1100 references to the primary literature are cited. Prokaryotic Gene Expression is a comprehensive and authoritative review of current knowledge and research in the area. It is; essential reading for postgraduates and researchers in the field. Advanced undergraduates in biochemistry, molecular biology, and microbiology will also find this book useful.

Gene expression. --- Genes --- Genetic regulation --- Expression

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Gene expression --- Genes --- Genetic regulation --- Expression

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Scientists today have access to an unprecedented arsenal of high-tech tools that can be used to thoroughly characterize biological systems of interest. High-throughput “omics” technologies enable to generate enormous quantities of data at the DNA, RNA, epigenetic and proteomic levels. One of the major challenges of the post-genomic era is to extract functional information by integrating such heterogeneous high-throughput genomic data. This is not a trivial task as we are increasingly coming to understand that it is not individual genes, but rather biological pathways and networks that drive an organism’s response to environmental factors and the development of its particular phenotype. In order to fully understand the way in which these networks interact (or fail to do so) in specific states (disease for instance), we must learn both, the structure of the underlying networks and the rules that govern their behavior. In recent years there has been an increasing interest in methods that aim to infer biological networks. These methods enable the opportunity for better understanding the interactions between genomic features and the overall structure and behavior of the underlying networks. So far, such network models have been mainly used to identify and validate new interactions between genes of interest. But ultimately, one could use these networks to predict large-scale effects of perturbations, such as treatment by multiple targeted drugs. However, currently, we are still at an early stage of comprehending methods and approaches providing a robust statistical framework to quantitatively assess the quality of network inference and its predictive potential. The scope of this Research Topic in Bioinformatics and Computational Biology aims at addressing these issues by investigating the various, complementary approaches to quantify the quality of network models. These “validation” techniques could focus on assessing quality of specific interactions, global and local structures, and predictive ability of network models. These methods could rely exclusively on in silico evaluation procedures or they could be coupled with novel experimental designs to generate the biological data necessary to properly validate inferred networks.

Validation --- Gene Expression --- Network Inference --- bioinformatics