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This book provides a comprehensive overview of different biomedical data types, including both clinical and genomic data. Thorough explanations enable readers to explore key topics ranging from electrocardiograms to Big Data health mining and EEG analysis techniques. Each chapter offers a summary of the field and a sample analysis. Also covered are telehealth infrastructure, healthcare information association rules, methods for mass spectrometry imaging, environmental biodiversity, and the global nonlinear fitness function for protein structures. Diseases are addressed in chapters on functional annotation of lncRNAs in human disease, metabolomics characterization of human diseases, disease risk factors using SNP data and Bayesian methods, and imaging informatics for diagnostic imaging marker selection. With the exploding accumulation of Electronic Health Records (EHRs), there is an urgent need for computer-aided analysis of heterogeneous biomedical datasets. Biomedical data is notorious for its diversified scales, dimensions, and volumes, and requires interdisciplinary technologies for visual illustration and digital characterization. Various computer programs and servers have been developed for these purposes by both theoreticians and engineers. This book is an essential reference for investigating the tools available for analyzing heterogeneous biomedical data. It is designed for professionals, researchers, and practitioners in biomedical engineering, diagnostics, medical electronics, and related industries.
In recent decades, new technologies have made remarkable progress in helping to understand biological systems. Rapid advances in genomic profiling techniques such as microarrays or high-performance sequencing have brought new opportunities and challenges in the fields of computational biology and bioinformatics. Such genetic sequencing techniques allow large amounts of data to be produced, whose analysis and cross-integration could provide a complete view of organisms. As a result, it is necessary to develop new techniques and algorithms that carry out an analysis of these data with reliability and efficiency. This Special Issue collected the latest advances in the field of computational methods for the analysis of gene expression data, and, in particular, the modeling of biological processes. Here we present eleven works selected to be published in this Special Issue due to their interest, quality, and originality.
Highlights the importance and benefit of mass spectrometry-based metabolomics for identifying biomarkers that accurately screen for potential biomarkers of diseases Mass spectrometry-based metabolomics offer new opportunities for biomarker discovery in complex diseases and may provide pathological understanding of diseases beyond traditional technologies. It is the systematic analysis of low-molecular-weight metabolites in biological samples and has been applied to discovering and identifying the perturbed pathways. Currently, mass spectrometry-based metabolomics has become an important tool in clinical research and the diagnosis of human disease. Mass Spectrometry-Based Metabolomics in Clinical and Herbal Medicines comprehensively presents the current state, challenges, and applications of high-throughput mass spectrometry-based metabolomics such as metabolites analysis, biomarker discovery, technical challenges, discovery of natural product, mechanism interpretation of action, discovery of active ingredients, clinical application and precision medicine, and enhancing their biomedical value in a real world of biomedicine, shedding light on the potential for spectrometry-based metabolomics. It highlights the value of mass spectrometry-based metabolomics and metabolism to address the complexity of herbal medicines in systems pharmacology, especially, to link phytochemical analysis with the assessment of pharmacological effect and therapeutic potential. Each chapter has been laid out with introduction, method, up-to-date literature, identification of biomarker, and applications Covers the current state, challenges, and applications of high-throughput mass spectrometry-based metabolomics in the discovery of biomarker, active ingredients, natural product, etc. Constitutes a unique and indispensable practical guide for any phytochemistry or related laboratory, and provides hands-on description of new techniques Provides a guide for new practitioners of pharmacologists, pharmacological scholars, drug developers, botanist, researchers of traditional medicines. Mass Spectrometry-Based Metabolomics in Clinical and Herbal Medicines provides a landmark of mass spectrometry-based metabolomics research and a beneficial guideline to graduate students and researchers in academia, industry, and technology transfer organizations in all biomedical science fields.
Computational chemistry is a means of applying theoretical ideas using computers and a set of techniques for investigating chemical problems within which common questions vary from molecular geometry to the physical properties of substances. Theory and Applications of Computational Chemistry: The First Forty Years is a collection of articles on the emergence of computational chemistry. It shows the enormous breadth of theoretical and computational chemistry today and establishes how theory and computation have become increasingly linked as methodologies and technologies have advanced. Written by the pioneers in the field, the book presents historical perspectives and insights into the subject, and addresses new and current methods, as well as problems and applications in theoretical and computational chemistry. Easy to read and packed with personal insights, technical and classical information, this book provides the perfect introduction for graduate students beginning research in this area. It also provides very readable and useful reviews for theoretical chemists.* Written by well-known leading experts * Combines history, personal accounts, and theory to explain much of the field of theoretical and compuational chemistry* Is the perfect introduction to the field
This book is indexed in Chemical Abstracts ServiceThe interactions of proteins with other molecules are important in many cellular activities. Investigations have been carried out to understand the recognition mechanism, identify the binding sites, analyze the the binding affinity of complexes, and study the influence of mutations on diseases. Protein interactions are also crucial in structure-based drug design.This book covers computational analysis of protein-protein, protein-nucleic acid and protein-ligand interactions and their applications. It provides up-to-date information and the latest developments from experts in the field, using illustrations to explain the key concepts and applications. This volume can serve as a single source on comparative studies of proteins interacting with proteins/DNAs/RNAs/carbohydrates and small molecules.
In the last few decades, near-infrared (NIR) spectroscopy has distinguished itself as one of the most rapidly advancing spectroscopic techniques. Mainly known as an analytical tool useful for sample characterization and content quantification, NIR spectroscopy is essential in various other fields, e.g. NIR imaging techniques in biophotonics, medical applications or used for characterization of food products. Its contribution in basic science and physical chemistry should be noted as well, e.g. in exploration of the nature of molecular vibrations or intermolecular interactions. One of the current development trends involves the miniaturization and simplification of instrumentation, creating prospects for the spread of NIR spectrometers at a consumer level in the form of smartphone attachments—a breakthrough not yet accomplished by any other analytical technique. A growing diversity in the related methods and applications has led to a dispersion of these contributions among disparate scientific communities. The aim of this Special Issue was to bring together the communities that may perceive NIR spectroscopy from different perspectives. It resulted in 30 contributions presenting the latest advances in the methodologies essential in near-infrared spectroscopy in a variety of applications.
Data Analysis for Omic Sciences: Methods and Applications, Volume 82, shows how these types of challenging datasets can be analyzed. Examples of applications in real environmental, clinical and food analysis cases help readers disseminate these approaches. Chapters of note include an Introduction to Data Analysis Relevance in the Omics Era, Omics Experimental Design and Data Acquisition, Microarrays Data, Analysis of High-Throughput RNA Sequencing Data, Analysis of High-Throughput DNA Bisulfite Sequencing Data, Data Quality Assessment in Untargeted LC-MS Metabolomic, Data Normalization and Scaling, Metabolomics Data Preprocessing, and more. - Presents the best reference book for omics data analysis - Provides a review of the latest trends in transcriptomics and metabolomics data analysis tools - Includes examples of applications in research fields, such as environmental, biomedical and food analysis
This graduate text covers a variety of mathematical and statistical tools for the analysis of big data coming from biology, medicine and economics. Neural networks, Markov chains, tools from statistical physics and wavelet analysis are used to develop efficient computational algorithms, which are then used for the processing of real-life data using Matlab.
This book gathers knowledge about matrix-assisted laser desorption ionisation (MALDI) mass spectrometry imaging for postgraduate and professional researchers in academia and in industry where it has direct application to clinical research.