Babak Sokouti – författare

Systems Biology and In-Depth Applications for Unlocking Diseases provides the essence of systems biology approaches in a practical manner illustrating the basic principles essential to develop and model in real life science applications. Methodologies covered show how to interrogate biological data, with the purpose of obtaining insight about disease diagnosis, prognosis, and treatment.Systematically written in 4 parts, this book first provides an introduction and history of systems biology; second, it provides the tools and resources needed for the structure and function of biological systems; next, it provides the evidence of systems biology in action to better understand disease connections; and finally, it provides the extensions of systems biology in various scientific fields including pharmacology, immunology, vaccinology, neuroscience, virology, and medicine. Examples include big data techniques, scale networks, mathematical model development, and much more.This is the perfect reference to provide the fundamental base of knowledge needed for systems biologists, professionals in systems medicine, computational biologists, and bioinformaticians, whether needed for immediate application or for building a comprehensive understanding of the field.

Provides detailed and comprehensive coverage of the field of systems biologyDelivers instruction on how to interrogate biological data, with the purpose of obtaining insight about disease diagnosis, prognosis, and treatmentMakes effective steps towards personalized medicine in the treatment of diseaseExplains effective disease treatment strategies at early diagnosis stages

Systems Biology and In-Depth Applications for Unlocking Diseases provides the essence of systems biology approaches in a practical manner illustrating the basic principles essential to develop and model in real life science applications. Methodologies covered show how to interrogate biological data, with the purpose of obtaining insight about disease diagnosis, prognosis, and treatment.Systematically written in 4 parts, this book first provides an introduction and history of systems biology; second, it provides the tools and resources needed for the structure and function of biological systems; next, it provides the evidence of systems biology in action to better understand disease connections; and finally, it provides the extensions of systems biology in various scientific fields including pharmacology, immunology, vaccinology, neuroscience, virology, and medicine. Examples include big data techniques, scale networks, mathematical model development, and much more.This is the perfect reference to provide the fundamental base of knowledge needed for systems biologists, professionals in systems medicine, computational biologists, and bioinformaticians, whether needed for immediate application or for building a comprehensive understanding of the field.- Provides detailed and comprehensive coverage of the field of systems biology- Delivers instruction on how to interrogate biological data, with the purpose of obtaining insight about disease diagnosis, prognosis, and treatment- Makes effective steps towards personalized medicine in the treatment of disease- Explains effective disease treatment strategies at early diagnosis stages

Generally speaking, quantitative-structure activity relationship (QSAR) is a technique which correlates the biological activities of a set of compounds to their structures using a mathematical equation represented in its general form by Biological Activity = f (x1, ..., xn), where f is a mathematical function and x1, ..., xn are n molecular descriptors. Since the introduction of the initial concept of QSAR in the early 1960s, numerous advances have been introduced into the field transforming it into an essential tool in drug discovery and medicinal chemistry. Quantitative Structure – Activity Relationship: A Practical Approach provides a detailed overview of computational approaches in QSAR studies. It covers the applications of different algorithms in various steps of a QSAR analysis and shows clear examples. Each chapter introduces the tools and software involved. Moreover, challenges and issues which may be faced in any step of the analysis are thoroughly broken down based on the OECD guidelines, enabling the reader to familiarize themselves with potential end results. The book was kept concise, making it suitable for students (pharmacy, chemistry and biological science) and lecturers, as well as researchers in the field.

Generally speaking, quantitative-structure activity relationship (QSAR) is a technique which correlates the biological activities of a set of compounds to their structures using a mathematical equation represented in its general form by Biological Activity = f (x1, ..., xn), where f is a mathematical function and x1, ..., xn are n molecular descriptors. Since the introduction of the initial concept of QSAR in the early 1960s, numerous advances have been introduced into the field transforming it into an essential tool in drug discovery and medicinal chemistry. Quantitative Structure – Activity Relationship: A Practical Approach provides a detailed overview of computational approaches in QSAR studies. It covers the applications of different algorithms in various steps of a QSAR analysis and shows clear examples. Each chapter introduces the tools and software involved. Moreover, challenges and issues which may be faced in any step of the analysis are thoroughly broken down based on the OECD guidelines, enabling the reader to familiarize themselves with potential end results. The book was kept concise, making it suitable for students (pharmacy, chemistry and biological science) and lecturers, as well as researchers in the field.