Kayhan Erciyes – författare

The brain consisting of billions of neurons is probably the most complex and mysterious organ of the body. Understanding the functioning of the brain in its health and disease states has baffled the researchers working in this area for many years. The diversity of brain diseases and disorders makes the analysis of brain functions an even more challenging area of research. In vitro and in vivo studies regarding the brain may be laborious, however, bioinformatics using in silico approaches may take the burden off the experimental studies and give us a clearer perspective on disease and healthy states of the brain, its functions, and disease mechanisms.

Recent advancements in neuroimaging technologies, the development of high-performance computers and the development of software, algorithms and methods to analyze data obtained from various neuroimaging processes have opened new frontiers in neuroscience enabling unprecedented finer analysis of the brain functions. This relatively new approach of brain analysis which may be termed Bioinformatics of the Brain is the main subject of this volume aiming to provide a thorough review of various bioinformatics approaches for analyzing the functioning of the brain and understanding brain diseases such as neurodegenerative diseases, brain tumors, and neuropsychiatric disorders. Authors from various disciplines in this volume each focus on a different aspect aiming to expand our understanding of this area of research. Topics included are:

This book is intended to aid scientists, researchers, and graduate students in carrying out interdisciplinary research in the areas of bioinformatics, bioengineering, computer engineering, software engineering, mathematics, molecular biology, genetics, and biotechnology.

The brain consisting of billions of neurons is probably the most complex and mysterious organ of the body. Understanding the functioning of the brain in its health and disease states has baffled the researchers working in this area for many years. The diversity of brain diseases and disorders makes the analysis of brain functions an even more challenging area of research. In vitro and in vivo studies regarding the brain may be laborious, however, bioinformatics using in silico approaches may take the burden off the experimental studies and give us a clearer perspective on disease and healthy states of the brain, its functions, and disease mechanisms.

Recent advancements in neuroimaging technologies, the development of high-performance computers and the development of software, algorithms and methods to analyze data obtained from various neuroimaging processes have opened new frontiers in neuroscience enabling unprecedented finer analysis of the brain functions. This relatively new approach of brain analysis which may be termed Bioinformatics of the Brain is the main subject of this volume aiming to provide a thorough review of various bioinformatics approaches for analyzing the functioning of the brain and understanding brain diseases such as neurodegenerative diseases, brain tumors, and neuropsychiatric disorders. Authors from various disciplines in this volume each focus on a different aspect aiming to expand our understanding of this area of research. Topics included are:

This book is intended to aid scientists, researchers, and graduate students in carrying out interdisciplinary research in the areas of bioinformatics, bioengineering, computer engineering, software engineering, mathematics, molecular biology, genetics, and biotechnology.

This unique textbook/reference presents unified coverage of bioinformatics topics relating to both biological sequences and biological networks, providing an in-depth analysis of cutting-edge distributed algorithms, as well as of relevant sequential algorithms. In addition to introducing the latest algorithms in this area, more than fifteen new distributed algorithms are also proposed. Topics and features: reviews a range of open challenges in biological sequences and networks; describes in detail both sequential and parallel/distributed algorithms for each problem; suggests approaches for distributed algorithms as possible extensions to sequential algorithms, when the distributed algorithms for the topic are scarce; proposes a number of new distributed algorithms in each chapter, to serve as potential starting points for further research; concludes each chapter with self-test exercises, a summary of the key points, a comparison of the algorithms described, and a literature review.