Bioinformatics of the Brain

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: Brain diseases and disorders Stem cell therapy of neurodegenerative diseases Tissue engineering applications of gliomas Brain tumor detection and modeling Brain tumor growth simulation Brain-computer interface Bioinformatics of brain diseases Graph-theoretical analysis of complex brain networks Brain proteomics 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.

Table of Contents:
Preface. About the Editors. List of Contributors. 1 BRAIN DISEASES AND DISORDERS. 2 Therapeutic Potential Of Stem Cells In Neurodegenerative Diseases. 3 Tissue Engineered Models of Brain Tumors and Their Applications. 4 BrainTumorDetectionUsingImageProcessingTechniques. 5 Tumor Growth Simulation. 6 Mathematical Modelling for Brain Tumors Including Fractional Operator. 7 EEG-based BCI systems in Neuropsychiatric Diseases. 8 Bioinformatics of Brain Diseases. 9 Complex Brain Networks: A Graph-Theoretical Analysis. 10 Brain Proteomics. Index

About the Author :
Kayhan Erciyes holds a B.Sc. (Hons.) in Electrical Engineering and Electronics from the University of Manchester Institute of Science and Technology, England, an M.Sc. degree in Electronic Control Engineering from the University of Salford, England and a Ph.D. degree in Computer Engineering from Ege University, Turkiye with part of the Ph.D. study realized at Edinburgh University, Scotland. He has worked as a professor in a number of institutions including Ege University, Yasar University, Uskudar University, Izmir Institute of Technology , UC Davis, Oregon State University, and California State University San Marcos. He is currently working at Computer Engineering Dept. Yaşar University, İzmir, and has published several books including Distributed and Sequential Algorithms for Bioinformatics by Springer Computational Biology Series. His research interests are broadly in graph theory and its applications in bioinformatics and brain networks, and parallel and distributed algorithms. Tuba Sevimoglu holds a B.Sc. in Chemical Engineering from Yildiz Technical University, Turkiye, an M.Sc. degree in Industrial Engineering from Florida International University, USA, and a Ph.D. degree in Bioengineering from Marmara University, Turkiye. She is currently a professor of Bioengineering at University of Health Sciences in Istanbul, Turkiye. Her research interests include bioinformatics approaches to analyzing big data, gene expression, biological networks and the bioinformatics of genetic, neurodegenerative, and autoimmune diseases.