HealthTech Horizons provides a concise yet comprehensive view of how cutting-edge technologies are transforming healthcare. Covering AI and machine learning in diagnostics, deep learning architectures (CNNs, RNNs, GANs) for genomics and imaging, synthetic data augmentation, and optimization algorithms (MRMR, EHO, HHWO) for complex biomedical datasets, this book bridges research with real-world applications.It also examines the disruptive rise of deepfake technologies and the metave...

In today’s data-driven world, biology and medicine are being transformed by the power of big data. Making sense of large, complicated biological datasets is a crucial problem that underlies every medical advancement and gene discovery. Feature Selection and Feature Extraction on Omics Data provides insight into this innovative area where biological science and computational science collide. This book, which is written in an approachable manner, explains the methods researchers emp...

This book focuses on an eminent technology called next generation sequencing (NGS) which has entirely changed the procedure of examining organisms and will have a great impact on biomedical research and disease diagnosis. Numerous computational challenges have been brought on by the rapid advancement of large-scale next-generation sequencing (NGS) technologies and their application. The term ""biomedical imaging"" refers to the use of a variety of imaging techniques (such as X-rays, CT sca...

Molecular understanding of cancer and cancer progression is at the forefront of many research programs today. High-throughput array technologies and other modern molecular techniques produce a wealth of molecular data about the structure, and function of cells, tissues, and organisms. Correctly analyzed and interpreted these data hold the promise of bringing new markers for prognostic and diagnostic use, for new treatment schemes, and of gaining new biological insight into the evolution of...

Providing genome-informed personalized treatment is a goal of modern medicine. Identifying new translational targets in nucleic acid characterizations is an important step toward that goal. The information tsunami produced by such genome-scale investigations is stimulating parallel developments in statistical methodology and inference, analytical frameworks, and computational tools. Within the context of genomic medicine and with a strong focus on cancer research, this book describes the i...

Big data, genomics, and quantitative approaches to network-based analysis are combining to advance the frontiers of medicine as never before. Network Medicine introduces this rapidly evolving field of medical research, which promises to revolutionize the diagnosis and treatment of human diseases. With contributions from leading experts that highlight the necessity of a team-based approach in network medicine, this definitive volume provides readers with a state-of-the-art synthesi...

Using chips composed of thousands of spots, each with the capability of holding DNA molecules corresponding to a given gene, DNA microarray technology has enabled researchers to measure simultaneously gene expression across the genome. As with other large-scale genomics approaches, microarray technologies are broadly applicable across disciplines of life and biomedical sciences, but remain daunting to many researchers. This guide is designed to demystify the technology and inform more biol...

This book serves as an introduction to the myriad computational approaches to gene regulatory modeling and analysis, and is written specifically with experimental biologists in mind. Mathematical jargon is avoided and explanations are given in intuitive terms. In cases where equations are unavoidable, they are derived from first principles or, at the very least, an intuitive description is provided. Extensive examples and a large number of model descriptions are provided for use in both cl...

New insights into the evolution and nature of proteinsExploring several distinct approaches, this book describes the methods for comparing protein sequences and protein structures in order to identify homologous relationships and classify proteins and protein domains into evolutionary families. Readers will discover the common features as well as the key philosophical differences underlying the major protein classification systems, including Pfam, Panther, SCOP, and CATH. Moreover,...

This ready reference discusses different methods for statistically analyzing and validating data created with high-throughput methods. As opposed to other titles, this book focusses on systems approaches, meaning that no single gene or protein forms the basis of the analysis but rather a more or less complex biological network. From a methodological point of view, the well balanced contributions describe a variety of modern supervised and unsupervised statistical methods applied to various...

Advances in high-throughput biological methods have led to the publication of a large number of genome-wide studies in human and animal models. In this context, recent tools from bioinformatics and computational biology have been fundamental for the analysis of these genomic studies. The book Bioinformatics and Human Genomics Research provides updated and comprehensive information about multiple approaches of the application of bioinformatic tools to research in human genomics. It...

The book introduces to the reader a number of cutting edge statistical methods which can e used for the analysis of genomic, proteomic and metabolomic data sets. In particular in the field of systems biology, researchers are trying to analyze as many data as possible in a given biological system (such as a cell or an organ). The appropriate statistical evaluation of these large scale data is critical for the correct interpretation and different experimental approaches require different app...