Madhu Chetty – författare

This book comprises eight chapters covering various aspects of healthcare. Initial chapters provide the basics of AI and molecular biology required to understand the more advanced topics. Later chapters cover key important aspects of bioinformatics such as modelling paradigms for biological processes, synthetic biology, and drug discovery, including case studies related to topics including cancer, ocular disease, and mental health. The book is relevant and timely.Artificial Intelligence (AI) is a very promising area of research and there is considerable interest in its application to a wide range of issues in the healthcare sector. However, many users of this technology do not have a good grasp of the key underlying principles of this technology. Although there are several resources already available in this area providing necessary content, they tend to be over-simplified, and demonstrate how to use applications, rather than the underlying principles. This book is intended to contribute as both a textbook and a demonstration of the way in which the AI algorithms can be applied. It will address the drawbacks in some of the current resources, as well as emphasize the benefits of the use of AI in this important field.

This book comprises eight chapters covering various aspects of healthcare. Initial chapters provide the basics of AI and molecular biology required to understand the more advanced topics. Later chapters cover key important aspects of bioinformatics such as modelling paradigms for biological processes, synthetic biology, and drug discovery, including case studies related to topics including cancer, ocular disease, and mental health. The book is relevant and timely. Artificial Intelligence (AI) is a very promising area of research and there is considerable interest in its application to a wide range of issues in the healthcare sector. However, many users of this technology do not have a good grasp of the key underlying principles of this technology. Although there are several resources already available in this area providing necessary content, they tend to be over-simplified, and demonstrate how to use applications, rather than the underlying principles. This book is intended to contribute as both a textbook and a demonstration of the way in which the AI algorithms can be applied. It will address the drawbacks in some of the current resources, as well as emphasize the benefits of the use of AI in this important field.

In the post-genomic era, a holistic understanding of biological systems and p- cesses,inalltheircomplexity,is criticalincomprehendingnature’schoreography of life. As a result, bioinformatics involving its two main disciplines, namely, the life sciences and the computational sciences, is fast becoming a very promising multidisciplinary research ?eld. With the ever-increasing application of lar- scalehigh-throughputtechnologies,suchasgeneorproteinmicroarraysandmass spectrometry methods, the enormous body of information is growing rapidly. Bioinformaticians are posed with a large number of di?cult problems to solve, arising not only due to the complexities in acquiring the molecular infor- tion but also due to the size and nature of the generated data sets and/or the limitations of the algorithms required for analyzing these data. Although the ?eld of bioinformatics is still in its embryonic stage, the recent advancements in computational and information-theoretic techniques are enablingus to c- ductvariousinsilicotestingandscreeningofmanylab-basedexperimentsbefore these are actually performed in vitro or in vivo. These in silico investigations are providing new insights for interpretation and establishing a new direction for a deeper understanding. Among the various advanced computational methods currently being applied to such studies, the pattern recognition techniques are mostly found to be at the core of the whole discovery process for apprehending the underlying biological knowledge. Thus, we can safely surmise that the - going bioinformatics revolution may, in future, inevitably play a major role in many aspects of medical practice and/or the discipline of life sciences.

In the post-genomic era, a holistic understanding of biological systems and p- cesses,inalltheircomplexity,is criticalincomprehendingnature’schoreography of life. As a result, bioinformatics involving its two main disciplines, namely, the life sciences and the computational sciences, is fast becoming a very promising multidisciplinary research ?eld. With the ever-increasing application of lar- scalehigh-throughputtechnologies,suchasgeneorproteinmicroarraysandmass spectrometry methods, the enormous body of information is growing rapidly. Bioinformaticians are posed with a large number of di?cult problems to solve, arising not only due to the complexities in acquiring the molecular infor- tion but also due to the size and nature of the generated data sets and/or the limitations of the algorithms required for analyzing these data. Although the ?eld of bioinformatics is still in its embryonic stage, the recent advancements in computational and information-theoretic techniques are enablingus to c- ductvariousinsilicotestingandscreeningofmanylab-basedexperimentsbefore these are actually performed in vitro or in vivo. These in silico investigations are providing new insights for interpretation and establishing a new direction for a deeper understanding. Among the various advanced computational methods currently being applied to such studies, the pattern recognition techniques are mostly found to be at the core of the whole discovery process for apprehending the underlying biological knowledge. Thus, we can safely surmise that the - going bioinformatics revolution may, in future, inevitably play a major role in many aspects of medical practice and/or the discipline of life sciences.