Providing an interface between dry-bench bioinformaticians and wet-lab biologists, DNA Methylation Microarrays: Experimental Design and Statistical Analysis presents the statistical methods and tools to analyze high-throughput epigenomic data, in particular, DNA methylation microarray data. Since these microarrays share the same underlying principles as gene expression microarrays, many of the analyses in the text also apply to microarray-based gene expression and histone modification (ChIP-on-chip) studies. After introducing basic statistics, the book describes wet-bench technologies that produce the data for analysis and explains how to preprocess the data to remove systematic artifacts resulting from measurement imperfections. It then explores differential methylation and genomic tiling arrays. Focusing on exploratory data analysis, the next several chapters show how cluster and network analyses can link the functions and roles of unannotated DNA elements with known ones. The book concludes by surveying the open source software (R and Bioconductor), public databases, and other online resources available for microarray research. Requiring only limited knowledge of statistics and programming, this book helps readers gain a solid understanding of the methodological foundations of DNA microarray analysis.

Books on computation in the marketplace tend to discuss the topics within specific fields. Many computational algorithms, however, share common roots. Great advantages emerge if numerical methodologies break the boundaries and find their uses across disciplines. Interdisciplinary Computing In Java Programming Language introduces readers of different backgrounds to the beauty of the selected algorithms. Serious quantitative researchers, writing customized codes for computation, enjoy cracking source codes as opposed to the black-box approach. Most C and Fortran programs, despite being slightly faster in program execution, lack built-in support for plotting and graphical user interface. This book selects Java as the platform where source codes are developed and applications are run, helping readers/users best appreciate the fun of computation. Interdisciplinary Computing In Java Programming Language is designed to meet the needs of a professional audience composed of practitioners and researchers in science and technology. This book is also suitable for senior undergraduate and graduate-level students in computer science, as a secondary text.

Books on computation in the marketplace tend to discuss the topics within specific fields. Many computational algorithms, however, share common roots. Great advantages emerge if numerical methodologies break the boundaries and find their uses across disciplines. Interdisciplinary Computing In Java Programming Language introduces readers of different backgrounds to the beauty of the selected algorithms. Serious quantitative researchers, writing customized codes for computation, enjoy cracking source codes as opposed to the black-box approach. Most C and Fortran programs, despite being slightly faster in program execution, lack built-in support for plotting and graphical user interface. This book selects Java as the platform where source codes are developed and applications are run, helping readers/users best appreciate the fun of computation.

Interdisciplinary Computing In Java Programming Language is designed to meet the needs of a professional audience composed of practitioners and researchers in science and technology. This book is also suitable for senior undergraduate and graduate-level students in computer science, as a secondary text.

Providing an interface between dry-bench bioinformaticians and wet-lab biologists, DNA Methylation Microarrays: "Experimental Design and Statistical Analysis" presents the statistical methods and tools to analyze high-throughput epigenomic data, in particular, DNA methylation microarray data. Since these microarrays share the same underlying principles as gene expression microarrays, many of the analyses in the text also apply to microarray-based gene expression and histone modification (ChIP-on-chip) studies.

After introducing basic statistics, the book describes wet-bench technologies that produce the data for analysis and explains how to preprocess the data to remove systematic artifacts resulting from measurement imperfections. It then explores differential methylation and genomic tiling arrays. Focusing on exploratory data analysis, the next several chapters show how cluster and network analyses can link the functions and roles of unannotated DNA elements with known ones. The book concludes by surveying the open source software (R and Bioconductor), public databases, and other online resources available for microarray research.

Requiring only limited knowledge of statistics and programming, this book helps readers gain a solid understanding of the methodological foundations of DNA microarray analysis.

Dogs eat grass, and so do cats. Every pet owner must have noticed the grass-eating behavior of their pets. Since wild dogs and cats eat grass too, most experts believe it to be an example of evolved traits of dogs and cats to relieve their upset gastro-intestines. Based on the observation, experts go on to suggest pet owners grow in their gardens medicinal herbs, other than botanicals that could be toxic to their pets. The herbal recipes, with doses, introduced in the book are intended for the most prevalent health problems of dogs and cats; the herbs that make up the recipes are: 1) available, as dietary supplements in the U.S., in the market by cGMP-certified manufacturers; and 2) in a dosage form of granules that is easy for pets to ingest. The book therefore not only meets experts' recommendations but also fulfils veterinarians' demand of an herbal pharmacopoeia for the widest conditions of their patients. Unlike other similar titles, the book is data-driven, quantitative, collective, comprehensive and practical: Although the herbs in the book have been used in traditional Chinese herbal medicine, owing to the data-driven approach of the book, no prior knowledge of Chinese or western herbal medicines is required to comprehend the book. The second feature of the book is that every indicated health condition of an herb comes with a score. The higher the score, the more frequently herbal clinicians have prescribed the herb (or herb pair) for the diagnosed condition in humans and thus the more likely that the herb (herb pair) is effective in mitigating the condition. The book is therefore quantitative, in contrast to other books which are qualitative. The third feature of the book is that the mapping from herbs and herb pairs to health conditions results from the collective experiences and expertise of the five thousand herbal clinicians in Taiwan, rather than the experience or expertise of a single doctor as in most other books. Without the deep learning/artificial intelligence techniques employed by the author on millions of (human) health insurance data, the aforementioned features are impossible. The final unique feature of the book is that recipes for the 94 most common conditions in dogs and 81 most common conditions in cats are given in later parts of the book, serving as reinforcing examples after going through the first part. The book is therefore both comprehensive and practical for not only holistic but also conventional veterinary professionals.

Modern Western Medicine (MWM) and Ayurveda/Traditional Chinese Medicine (TCM) can be considered two extreme paradigms to complex systems. The microscopic and reductionist approach of the West prevails in acute and single-gene conditions such as infection and Mendelian disorders. The macroscopic and holistic approach of the East potentially fares well at chronic and complex conditions such as obesity and ageing. The book serves three purposes: 1) to help MWM, Ayurveda and TCM professionals get acquainted with one another; 2) to help identify common grounds for MWM, Ayurveda and TCM, rather than blindly westernizing eastern medicines or vice versa; and 3) to help translate the complementarity of MWM and Ayurveda/TCM toward an integrative multi-component healthcare. To this end, we introduce theories and tenets of the three medicines. We use bioenergetics to reconcile West and East as ATP generation, prana and qi are central to MWM, Ayurveda and TCM. We discuss clinical trials of varying experimental rigors for the assessment of the scientific evidence for treatment effectiveness. We present complementary interventions for chronic disorders and ageing. We hold that a federal unity of therapies consisting of MWM, Ayurveda and TCM better serves the wellbeing of humankind.

Since AlphaGo defeated Ke Jie (who was then ranked 1st among all human players worldwide) May 2017, the art of Go (otherwise known as Weiqi) has entered a new era. Similarly, if we apply artificial intelligence (AI) to herbal medicine, the art of herbal prescription can experience a game change too. The author of this book has done exactly that, and via reverse engineering of the trained AI, the book details how one can compose herbal prescriptions from scratch.As artificial intelligence (AI) technologies outperform humans in such tasks as image/voice recognition and language translation, mastering of concentrated herbal extract granules (CHEG) prescription composition by AI is not a fiction, provided large quantities of high-quality CHEG prescription data are available. Thanks to the 340 million records of modern Western medicine diagnoses and corresponding CHEG prescriptions in the National Health Insurance Reimbursement Database (Taiwan) recorded in the decade between 2004 and 2013, the book is based on the results of applying state-of-the-art deep learning technologies to the CHEG prescription big data.