Complexity Science Living Systems And Reflexing Interfaces New Models And Perspectives
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Complexity Science, Living Systems, and Reflexing Interfaces: New Models and Perspectives
There are new and important advancements in todays complexity theories in ICT and requires an extraordinary perspective on the interaction between living systems and information technologies. With human evolution and its continuous link with the development of new tools and environmental changes, technological advancements are paving the way for new evolutionary steps. Complexity Science, Living Systems, and Reflexing Interfaces: New Models and Perspectives is a collection of research provided by academics and scholars aiming to introduce important advancements in areas such as artificial intelligence, evolutionary computation, neural networks, and much more. This scholarly piece will provide contributions that will define the line of development in complexity science.
Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology
Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology discusses the latest developments in all aspects of computational biology, bioinformatics, and systems biology and the application of data-analytics and algorithms, mathematical modeling, and simu- lation techniques. • Discusses the development and application of data-analytical and theoretical methods, mathematical modeling, and computational simulation techniques to the study of biological and behavioral systems, including applications in cancer research, computational intelligence and drug design, high-performance computing, and biology, as well as cloud and grid computing for the storage and access of big data sets. • Presents a systematic approach for storing, retrieving, organizing, and analyzing biological data using software tools with applications to general principles of DNA/RNA structure, bioinformatics and applications, genomes, protein structure, and modeling and classification, as well as microarray analysis. • Provides a systems biology perspective, including general guidelines and techniques for obtaining, integrating, and analyzing complex data sets from multiple experimental sources using computational tools and software. Topics covered include phenomics, genomics, epigenomics/epigenetics, metabolomics, cell cycle and checkpoint control, and systems biology and vaccination research. • Explains how to effectively harness the power of Big Data tools when data sets are so large and complex that it is difficult to process them using conventional database management systems or traditional data processing applications. - Discusses the development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological and behavioral systems. - Presents a systematic approach for storing, retrieving, organizing and analyzing biological data using software tools with applications. - Provides a systems biology perspective including general guidelines and techniques for obtaining, integrating and analyzing complex data sets from multiple experimental sources using computational tools and software.
Biochemistry, Biophysics, and Molecular Chemistry
Biochemistry, Biophysics, and Molecular Chemistry: Applied Research and Interactions provides the background needed in biophysics and molecular chemistry and offers a great deal of advanced biophysical knowledge. It emphasizes the growing interrelatedness of molecular chemistry and biochemistry, and acquaints one with experimental methods of both disciplines. This book addresses some of the enormous advances in biochemistry, particularly in the areas of structural biology and bioinformatics, by providing a solid biochemical foundation that is rooted in chemistry. Topics include scientific integrity and ethics in the field; clinical translational research in cancer, diabetes, and cardiovascular disease; emerging drugs to treat neurodegenerative diseases; swine, avian, and human flu; the use of big data in artificial knowledge in the field; bioinformatic insights on molecular chemistry; and much more.