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An Introduction to Generative Drug Discovery
This book focuses on the latest advances in computational de novo drug discovery methods, also known as generative drug discovery. This book describes the state‐of‐the‐art methods and applications for de novo design of drug candidates using generative chemistry models as well as the ethical aspects of this technology. It will provide a foundation for those new to the field as well as those that may already have some experience of its utility. With contributions from scientists in both academia and industry ‘an Introduction to Generative Drug Discovery’ may represent one of the earliest if not the first book to focus on this topic. This book focuses on the latest advances in generative discovery methods. This book will describe different state of the art applications of generative molecule design. The book describes ethical aspects of generative drug discovery technology. The mix of academic and industrial authors provides an array of applications of generative drug discovery. A future perspective of where these generative technologies may take us in drug discovery is described included self-driving labs.
Computational Approaches in Biotechnology and Bioinformatics
Volume 1 of Computational Approaches in Bioengineering—Computational Approaches in Biotechnology and Bioinformatics—explores many significant topics of biomedical engineering and bioinformatics in an easily understandable format. It explores recent developments and applications in bioinformatics, biomechanics, artificial intelligence (AI), signal processing, wearable sensors, biomaterials, cell biology, synthetic biology, biostatistics, prosthetics, big data, and algorithms. From applications of biomaterials in advanced drug delivery systems to the role of big data, AI, and machine learning in disease diagnosis and treatment, the book will help readers understand how these technologies a...
General Principles of Ecological Risk Assessment
The book provides a comprehensive and up-to-date overview of the most modern concepts and tools needed to perform prospective and retrospective ecological risk assessments of environmental stressors, and will therefore be useful for students, teachers, scientists, regulators, and professionals in environmental consulting. Experimental methods and predictive theoretical approaches are described to evaluate and estimate the exposure of ecosystems to environmental stressors and to investigate their effects on different hierarchical levels of ecological organization (individuals, populations, communities, ecosystems). Specific sections are dedicated to the persistence and bioavailability of contaminants, bioaccumulation models, and the mechanisms of global pollution. Risk assessment procedures for the most relevant classes of traditional and emerging stressors, including physical agents, are described in detail in specific sections. Finally, regulatory instruments and public perception of risk are discussed.
Machine Learning and Deep Learning in Computational Toxicology
This book is a collection of machine learning and deep learning algorithms, methods, architectures, and software tools that have been developed and widely applied in predictive toxicology. It compiles a set of recent applications using state-of-the-art machine learning and deep learning techniques in analysis of a variety of toxicological endpoint data. The contents illustrate those machine learning and deep learning algorithms, methods, and software tools and summarise the applications of machine learning and deep learning in predictive toxicology with informative text, figures, and tables that are contributed by the first tier of experts. One of the major features is the case studies of ap...
Exploring Molecular Targets to Treat Neurodegenerative Disorders
This book delves into the delicate realm of neurodegenerative illnesses, navigating the vast landscape of molecular targets with care and purpose. Researchers are studying the complex pathways involved in diseases such as Alzheimer’s, Parkinson’s, and Huntington’s in order to identify specific molecules that could be targeted for therapy. The present work explores potential methods of intervention by carefully analysing neural circuits, protein misfolding, and genetic predispositions, unravelling the complexities of the human mind by focusing on individual molecular targets. As new findings emerge, reducing the severe consequences of neurodegenerative illnesses becomes increasingly possible, providing optimism for millions of people throughout the world.
Nanoelectronics, Circuits and Communication Systems
This book features selected papers presented at Third International Conference on Nanoelectronics, Circuits and Communication Systems (NCCS 2017). Covering topics such as MEMS and nanoelectronics, wireless communications, optical communication, instrumentation, signal processing, Internet of Things, image processing, bioengineering, green energy, hybrid vehicles, environmental science, weather forecasting, cloud computing, renewable energy, RFID, CMOS sensors, actuators, transducers, telemetry systems, embedded systems, and sensor network applications in mines, it is a valuable resource for young scholars, researchers, and academics.
Data Science for Effective Healthcare Systems
Data Science for Effective Healthcare Systems has a prime focus on the importance of data science in the healthcare domain. Various applications of data science in the health care domain have been studied to find possible solutions. In this period of COVID-19 pandemic data science and allied areas plays a vital role to deal with various aspect of health care. Image processing, detection & prevention from COVID-19 virus, drug discovery, early prediction, and prevention of diseases are some thrust areas where data science has proven to be indispensable. Key Features: The book offers comprehensive coverage of the most essential topics, including: Big Data Analytics, Applications & Challenges in...
In Silico Methods for Drug Design and Discovery
This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.
TinyML for Edge Intelligence in IoT and LPWAN Networks
Recently, Tiny Machine Learning (TinyML) has gained incredible importance due to its capabilities of creating lightweight machine learning (ML) frameworks aiming at low latency, lower energy consumption, lower bandwidth requirement, improved data security and privacy, and other performance necessities. As billions of battery-operated embedded IoT and low power wide area networks (LPWAN) nodes with very low on-board memory and computational capabilities are getting connected to the Internet each year, there is a critical need to have a special computational framework like TinyML. TinyML for Edge Intelligence in IoT and LPWAN Networks presents the evolution, developments, and advances in TinyM...
Handbook of Bibliometric Indicators
At last, the first systematic guide to the growing jungle of citation indices and other bibliometric indicators. Written with the aim of providing a complete and unbiased overview of all available statistical measures for scientific productivity, the core of this reference is an alphabetical dictionary of indices and other algorithms used to evaluate the importance and impact of researchers and their institutions. In 150 major articles, the authors describe all indices in strictly mathematical terms without passing judgement on their relative merit. From widely used measures, such as the journal impact factor or the h-index, to highly specialized indices, all indicators currently in use in the sciences and humanities are described, and their application explained. The introductory section and the appendix contain a wealth of valuable supporting information on data sources, tools and techniques for bibliometric and scientometric analysis - for individual researchers as well as their funders and publishers.
