Advances In Methods And Tools For Multi Omics Data Analysis

Advances in methods and tools for multi-omics data analysis

Omics Technologies for Clinical Diagnosis and Gene Therapy: Medical Applications in Human Genetics

Genetic disorders have been the focus of scientists for a long time. The emergence of next-generation sequencing techniques has ushered a new era in genetics and several developments have occurred in human genetics. The scientific perspective has also been widened with omics technologies that allow researchers to analyze genetic sequences and their expression products. An integrated approach is being used not only for diagnosis but also for disease management and therapeutic purposes. This book highlights emerging areas of omics technology and its application in the diagnosis and management of human genetic disorders. The book covers three areas of research and implementation: 1) Diagnosis (covering conventional strategies to next-generation platforms). This section focuses on the role of in silico analysis, databases and multi-omics of single-cell which will help in designing better management strategies. 2) Disease Management and therapeutic interventions. This section starts with genetic counselling and progresses to more specific techniques such as pharmacogenomics and personalized medicine, gene editing techniques and their applications in gene therapies and regenerative medicine. 3) Case studies. This section discusses the applications and success of all the above-mentioned strategies on selected human disorders. This book serves as a handy reference for students and academics studying advanced omics techniques in biochemistry and molecular genetics as part of courses in life sciences, pharmacology and medicine.

Advanced AI Techniques and Applications in Bioinformatics

The advanced AI techniques are essential for resolving various problematic aspects emerging in the field of bioinformatics. This book covers the recent approaches in artificial intelligence and machine learning methods and their applications in Genome and Gene editing, cancer drug discovery classification, and the protein folding algorithms among others. Deep learning, which is widely used in image processing, is also applicable in bioinformatics as one of the most popular artificial intelligence approaches. The wide range of applications discussed in this book are an indispensable resource for computer scientists, engineers, biologists, mathematicians, physicians, and medical informaticists. Features: Focusses on the cross-disciplinary relation between computer science and biology and the role of machine learning methods in resolving complex problems in bioinformatics Provides a comprehensive and balanced blend of topics and applications using various advanced algorithms Presents cutting-edge research methodologies in the area of AI methods when applied to bioinformatics and innovative solutions Discusses the AI/ML techniques, their use, and their potential for use in common and future bioinformatics applications Includes recent achievements in AI and bioinformatics contributed by a global team of researchers