Найти книгу: "Biomedical Vibrational Spectroscopy"

This comprehensive overview of biomedical applications of vibrational spectroscopy focuses on methodologies that are most relevant to biodiagnostics. After a few introductory chapters that summarize the current status of the field, the reference covers current spectroscopic applications; new spectroscopic directions; and study design and the analysis of vibrational spectral fingerprints from complex biological and clinical samples . With chapters contributed by leading international experts, Biomedical Vibrational Spectroscopy is a core resource.

An essential guide to healthcare data problems, sources, and solutions Strategies in Biomedical Data Science provides medical professionals with much-needed guidance toward managing the increasing deluge of healthcare data. Beginning with a look at our current top-down methodologies, this book demonstrates the ways in which both technological development and more effective use of current resources can better serve both patient and payer. The discussion explores the aggregation of disparate data sources, current analytics and toolsets, the growing necessity of smart bioinformatics, and more as data science and biomedical science grow increasingly intertwined. You'll dig into the unknown challenges that come along with every advance, and explore the ways in which healthcare data management and technology will inform medicine, politics, and research in the not-so-distant future. Real-world use cases and clear examples are featured throughout, and coverage of data sources, problems, and potential mitigations provides necessary insight for forward-looking healthcare professionals. Big Data has been a topic of discussion for some time, with much attention focused on problems and management issues surrounding truly staggering amounts of data. This book offers a lifeline through the tsunami of healthcare data, to help the medical community turn their data management problem into a solution. Consider the data challenges personalized medicine entails Explore the available advanced analytic resources and tools Learn how bioinformatics as a service is quickly becoming reality Examine the future of IOT and the deluge of personal device data The sheer amount of healthcare data being generated will only increase as both biomedical research and clinical practice trend toward individualized, patient-specific care. Strategies in Biomedical Data Science provides expert insight into the kind of robust data management that is becoming increasingly critical as healthcare evolves.

This book presents a balance of theoretical considerations and practical problem solving of electrochemical impedance spectroscopy. This book incorporates the results of the last two decades of research on the theories and applications of impedance spectroscopy, including more detailed reviews of the impedance methods applications in industrial colloids, biomedical sensors and devices, and supercapacitive polymeric films. The book covers all of the topics needed to help readers quickly grasp how to apply their knowledge of impedance spectroscopy methods to their own research problems. It also helps the reader identify whether impedance spectroscopy may be an appropriate method for their particular research problem. This includes understanding how to correctly make impedance measurements, interpret the results, compare results with expected previously published results form similar chemical systems, and use correct mathematical formulas to verify the accuracy of the data. Unique features of the book include theoretical considerations for dealing with modeling, equivalent circuits, and equations in the complex domain, review of impedance instrumentation, best measurement methods for particular systems and alerts to potential sources of errors, equations and circuit diagrams for the most widely used impedance models and applications, figures depicting impedance spectra of typical materials and devices, extensive references to the scientific literature for more information on particular topics and current research, and a review of related techniques and impedance spectroscopy modifications.

This book introduces readers interested in the field of X-ray Photoelectron Spectroscopy (XPS) to the practical concepts in this field. The book first introduces the reader to the language and concepts used in this field and then demonstrates how these concepts are applied. Including how the spectra are produced, factors that can influence the spectra (all initial and final state effects are discussed), how to derive speciation, volume analysed and how one controls this (includes depth profiling), and quantification along with background substraction and curve fitting methodologies. This is presented in a concise yet comprehensive manner and each section is prepared such that they can be read independently of each other, and all equations are presented using the most commonly used units. Greater emphasis has been placed on spectral understanding/interpretation. For completeness sake, a description of commonly used instrumentation is also presented. Finally, some complementary surface analytical techniques and associated concepts are reviewed for comparative purposes in stand-alone appendix sections.

This text offers an open-learning approach to Raman spectroscopy providing detail on instrumentation, applications and discussions questions throughout the book. It provides a valuable guide to assist with teaching Raman spectroscopy which is gaining attention in (analytical) chemistry, and as a consequence, teaching programs have followed. Today, education in Raman spectroscopy is often limited to theoretical aspects (e.g. selection rules), but practical aspects are usually disregarded. With these course notes, the author hopes to fill this gap and include information about Raman instrumentation and how it is interpreted. Provides a user-friendly text that tackles the theoretical background, and offers everyday tips for common practice Raman instrumentation and practical aspects, which are sometimes overlooked, are covered Appropriate for students, and includes summaries, text boxes, illustrating the ideas with examples from research literature or providing background information or links with other courses Written with an open-learning approach, this book will be ideal for use as a self-study guide or as the basis of a taught course with discussion and self-assessment questions throughout the text Includes a comprehensive bibliography to guide the reader to more specialized texts and sources.

This book provides an essential understanding of statistical concepts necessary for the analysis of genomic and proteomic data using computational techniques. The author presents both basic and advanced topics, focusing on those that are relevant to the computational analysis of large data sets in biology. Chapters begin with a description of a statistical concept and a current example from biomedical research, followed by more detailed presentation, discussion of limitations, and problems. The book starts with an introduction to probability and statistics for genome-wide data, and moves into topics such as clustering, classification, multi-dimensional visualization, experimental design, statistical resampling, and statistical network analysis. Clearly explains the use of bioinformatics tools in life sciences research without requiring an advanced background in math/statistics Enables biomedical and life sciences researchers to successfully evaluate the validity of their results and make inferences Enables statistical and quantitative researchers to rapidly learn novel statistical concepts and techniques appropriate for large biological data analysis Carefully revisits frequently used statistical approaches and highlights their limitations in large biological data analysis Offers programming examples and datasets Includes chapter problem sets, a glossary, a list of statistical notations, and appendices with references to background mathematical and technical material Features supplementary materials, including datasets, links, and a statistical package available online Statistical Bioinformatics is an ideal textbook for students in medicine, life sciences, and bioengineering, aimed at researchers who utilize computational tools for the analysis of genomic, proteomic, and many other emerging high-throughput molecular data. It may also serve as a rapid introduction to the bioinformatics science for statistical and computational students and audiences who have not experienced such analysis tasks before.