This open access book brings out the state of the art on how informatics-based tools are used and expected to be used in nanomaterials research. There has been great progress in the area in which “big-data” generated by experiments or computations are fully utilized to accelerate discovery of new materials, key factors, and design rules. Data-intensive approaches play indispensable roles in advanced materials characterization. "Materials informatics" is the central paradigm in the new trend. "Nanoinformatics" is its essential subset, which focuses on nanostructures of materials such as surfaces, interfaces, dopants, and point defects, playing a critical role in determining materials properties. There have been significant advances in experimental and computational techniques to characterize individual atoms in nanostructures and to gain quantitative information. The collaboration of researchers in materials science and information science is growing actively and is creating a new trend in materials science and engineering.
This textbook for graduate and postgraduate students provides comprehensive applications of nanoparticles in medicine, agriculture, and environmental sciences. The initial chapter covers basic topics related to types, synthesis, structure, and properties of various nanoparticles. It further discusses the wide range of applications of nanoparticles in medicine, agriculture, and the environment. The book presents nano-electronic biosensors that are used to diagnose and monitor the progression of human diseases. It summarizes the opportunities and challenges of nanotechnology in the agriculture and food sector highlighting the scientific, technical, regulatory, safety, and societal impacts. Additionally, it illustrates the applications of nanotechnology in the field of aquaculture medicine, bioinformatics and food technology. The textbook examines the development and administration of nano-medicines , their applications, advantages, and limitations for the treatment and prophylaxis of a broad range of diseases. Lastly, the textbook explores the recent advances in the field of nanobusiness and nanotechnology issues in intellectual property management( IPR).
Nano-enabled Sustainable and Precision Agriculture is the first single-volume resource to cover this important field using a whole systems approach that considers both opportunities and challenges. The book provides a comprehensive understanding of the role of nanotechnology in agriculture from broad aspects, but also includes a comprehensive view of the interaction of nanomaterials with soil-plant systems. It highlights aspects not described in previous books, including the application of nanoinformatics and artificial intelligence in nano-enabled sustainable agriculture, the application of nanotechnology in alternative forms of agriculture such as hydroponics, and regulatory frameworks for this research field.The book addresses all these aspects by including sections on enhanced sustainability, reduced pollution and enhanced ecosystems' health, and the role of nanoinformatics and machine learning. - Provides foundational insights and resources for each area, including soil science, water chemistry, nanoscience, plant science, microbiology and nanoinformatics - Focuses on mechanisms of action, transformations and the underpinning chemistry and biochemistry - Includes linkages and cross-referencing between chapters to ensure a cohesive and comprehensive resource
Nanotechnology in Therapeutics Comprehensive reference delivering a framework to develop and assess nanosystems that provide unique advantages in biomedical applications Nanotechnology in Therapeutics explores the idea that by studying in depth the behavior of living organisms, especially the functionality of their cell membranes, we can develop and evaluate innovative bio-inspired nanosystems that are able to deliver small molecules, biomolecules like proteins, peptides, and other genetic material in terms of the production of new therapies and vaccines. The main concept promoted in this book is an integrated approach for producing new medicines following the nanotoxicity, biotoxicity, regulatory, and ethical guidelines, which are also covered in the book. The book is divided into three parts. Part A provides an introduction and a historical overview of nanotechnology. Part B delves deeper into issues relating to lipid and polymeric nanostructures in medicine. Part C presents the regulatory landscape around nanotechnology and nanomedicine, while highlighting the need to keep an eye on emerging technologies such as artificial intelligence and machine learning. Overall, this book opens up biomedical applications for previously challenging drugs and drug targets. Written by a highly qualified professor with significant pertinent research experience, Nanotechnology in Therapeutics includes discussion on: Eukaryotic cell membranes, their structural properties, and the thermodynamic payload of their lipid bilayers The DLVO (Derjaguin, Landau, Verwey and Overbeek) theory as a scientific tool for studying the stability and the behavior of nanoparticles Liposomes, lipid nanoparticles, and solid lipid nanoparticles, as well as polymeric nanoparticles, like micelles, polymersomes, and dendrimers Issues in the approval process of nanomedicines by the regulatory agencies, such as complexity, chaos, and nonlinear dynamics With comprehensive coverage of novel concepts that have the potential to transform how new medicines are designed and developed, Nanotechnology in Therapeutics is an essential resource on the subject for chemists in industry, as well as biomedical and pharmaceutical engineers.
Materials informatics: a 'hot topic' area in materials science, aims to combine traditionally bio-led informatics with computational methodologies, supporting more efficient research by identifying strategies for time- and cost-effective analysis. The discovery and maturation of new materials has been outpaced by the thicket of data created by new combinatorial and high throughput analytical techniques. The elaboration of this "quantitative avalanche"—and the resulting complex, multi-factor analyses required to understand it—means that interest, investment, and research are revisiting informatics approaches as a solution. This work, from Krishna Rajan, the leading expert of the informatics approach to materials, seeks to break down the barriers between data management, quality standards, data mining, exchange, and storage and analysis, as a means of accelerating scientific research in materials science. This solutions-based reference synthesizes foundational physical, statistical, and mathematical content with emerging experimental and real-world applications, for interdisciplinary researchers and those new to the field. - Identifies and analyzes interdisciplinary strategies (including combinatorial and high throughput approaches) that accelerate materials development cycle times and reduces associated costs - Mathematical and computational analysis aids formulation of new structure-property correlations among large, heterogeneous, and distributed data sets - Practical examples, computational tools, and software analysis benefits rapid identification of critical data and analysis of theoretical needs for future problems
Annotation The three volume set LNAI 5177, LNAI 5178, and LNAI 5179, constitutes the refereed proceedings of the 12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008, held in Zagreb, Croatia, in September 2008. The 316 revised papers presented were carefully reviewed and selected. The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; topics covered in the first volume are artificial neural networks and connectionists systems; fuzzy and neuro-fuzzy systems; evolutionary computation; machine learning and classical AI; agent systems; knowledge based and expert systems; intelligent vision and image processing; knowledge management, ontologies, and data mining; Web intelligence, text and multimedia mining and retrieval; and intelligent robotics and control.
This edited book provides information on emerging fields of next-generation healthcare informatics with a special emphasis on emerging developments and applications of artificial intelligence, deep learning techniques, computational intelligence methods, Internet of medical things (IoMT), optimization techniques, decision making, nanomedicine, and cloud computing. The book provides a conceptual framework and roadmap for decision-makers for this transformation. The chapters involved in this book cover challenges and opportunities for diabetic retinopathy detection based on deep learning applications, deep learning accelerators in IoT and IoMT, health data analysis, deep reinforcement-based conversational AI agent in healthcare systems, examination of health data performance, multisource data in intelligent medicine, application of genetic algorithms in health care, mental disorder, digital healthcare system with big data analytics, encryption methods in healthcare data security, computation and cognitive bias in healthcare intelligence and pharmacogenomics, guided imagery therapy, cancer detection and prediction techniques, medical image processing for coronavirus, and imbalance learning in health care.
The Handbook of Computational Neurodegeneration provides a comprehensive overview of the field and thus bridges the gap between standard textbooks of research on neurodegeneration and dispersed publications for specialists that have a narrowed focus on computational methods to study this complicated process. The handbook reviews the central issues and methodological approaches related to the field for which the reader pursues a thorough overview. It also conveys more advanced knowledge, thus serving both as an introductory text and as a starting point for an in-depth study of a specific area, as well as a quick reference source for the expert by reflecting the state of the art and future prospects. The book includes topics that are usually missing in standard textbooks and that are only marginally represented in the specific literature. The broad scope of this handbook is reflected by five major parts that facilitate an integration of computational concepts, methods and applications in the study of neurodegeneration. Each part is intended to stand on its own, giving an overview of the topic and the most important problems and approaches, which are supported by examples, practical applications, and proposed methodologies. The basic concepts and knowledge, standard procedures and methods are presented, as well as recent advances and new perspectives.
Applications of nanotechnology continue to fuel significant innovations in areas ranging from electronics, microcomputing, and biotechnology to medicine, consumer supplies, aerospace, and energy production. As progress in nanoscale science and engineering leads to the continued development of advanced materials and new devices, improved methods of modeling and simulation are required to achieve a more robust quantitative understanding of matter at the nanoscale. Computational Nanotechnology: Modeling and Applications with MATLAB® provides expert insights into current and emerging methods, opportunities, and challenges associated with the computational techniques involved in nanoscale research. Written by, and for, those working in the interdisciplinary fields that comprise nanotechnology—including engineering, physics, chemistry, biology, and medicine—this book covers a broad spectrum of technical information, research ideas, and practical knowledge. It presents an introduction to computational methods in nanotechnology, including a closer look at the theory and modeling of two important nanoscale systems: molecular magnets and semiconductor quantum dots. Topics covered include: Modeling of nanoparticles and complex nano and MEMS systems Theory associated with micromagnetics Surface modeling of thin films Computational techniques used to validate hypotheses that may not be accessible through traditional experimentation Simulation methods for various nanotubes and modeling of carbon nanotube and silicon nanowire transistors In regard to applications of computational nanotechnology in biology, contributors describe tracking of nanoscale structures in cells, effects of various forces on cellular behavior, and use of protein-coated gold nanoparticles to better understand protein-associated nanomaterials. Emphasizing the importance of MATLAB for biological simulations in nanomedicine, this wide-ranging survey of computational nanotechnology concludes by discussing future directions in the field, highlighting the importance of the algorithms, modeling software, and computational tools in the development of efficient nanoscale systems.
This new book takes an in-depth look at the emerging and prospective field of computational biology and bioinformatics, which possesses the ability to analyze large accumulated biological data collected from sequence analysis of proteins and genes and cell population with an aim to make new predictions pertaining to drug discovery and new biology. The book explains the basic methodology associated with a bioinformatics and computational approach in drug designing. It then goes on to cover the implementation of computational programming, bioinformatics, pharmacophore modeling, biotechnological techniques, and pharmaceutical chemistry in designing drugs. The major advantage of intervention of computer language or programming is to cut down the number of steps and costs in the field of drug designing, reducing the repeating steps and saving time in screening the potent component for drug or vaccine designing. The book describes algorithms used for drug designing and the use of machine learning and AI in drug delivery and disease diagnosis, which are valuable in clinical decision-making. The implementation of robotics in different diseases like stroke, cancer, COVID-19, etc. is also addressed. Topics include machine learning, AI, databases in drug design, molecular docking, bioinformatics tools, target-based drug design, and immunoinformatics, chemoinformatics, and nanoinformatics in drug design. Drug repurposing in drug design in general as well as for specific diseases, including cancer, Alzheimer’s disease, tuberculosis, COVID-19, etc., is also addressed in depth.
