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Many biological systems and objects are intrinsically fuzzy as their properties and behaviors contain randomness or uncertainty. In addition, it has been shown that exact or optimal methods have significant limitation in many bioinformatics problems. Fuzzy set theory and fuzzy logic are ideal to describe some biological systems/objects and provide good tools for some bioinformatics problems. This book comprehensively addresses several important bioinformatics topics using fuzzy concepts and approaches, including measurement of ontological similarity, protein structure prediction/analysis, and

Bioinformatics. --- Computational biology. --- Fuzzy logic. --- Fuzzy sets. --- Bio-informatics --- Biological informatics --- Biology --- Information science --- Computational biology --- Systems biology --- Nonlinear logic --- Fuzzy mathematics --- Logic, Symbolic and mathematical --- Fuzzy systems --- Bioinformatics --- Sets, Fuzzy --- Set theory --- Data processing

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Accounting --- Auditing

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Volume one of this two volume sequence focuses on the basic characterization of known protein structures as well as structure prediction from protein sequence information. The 11 chapters provide an overview of the field, covering key topics in modeling, force fields, classification, computational methods, and struture prediction. Each chapter is a self contained review designed to cover (1) definition of the problem and an historical perspective, (2) mathematical or computational formulation of the problem, (3) computational methods and algorithms, (4) performance results, (5) existing software packages, and (6) strengths, pitfalls, challenges, and future research directions.

Computational biology --- Proteins --- 577.122 --- 577.122 Protein metabolism --- Protein metabolism --- Proteids --- Biomolecules --- Polypeptides --- Proteomics --- Protein conformation --- Biology --- Bioinformatics --- Conformation --- Structure --- Structure&delete& --- Mathematical models --- Physics. --- Proteomics. --- Proteins. --- Bioinformatics. --- Biophysics. --- Biological physics. --- Biophysics and Biological Physics. --- Protein Science. --- Computational biology. --- Structure. --- Conformation. --- Mathematical models. --- Biochemistry. --- Biological and Medical Physics, Biophysics. --- Biological chemistry --- Chemical composition of organisms --- Organisms --- Physiological chemistry --- Chemistry --- Medical sciences --- Bio-informatics --- Biological informatics --- Information science --- Systems biology --- Molecular biology --- Composition --- Data processing --- Proteins . --- Biological physics --- Physics

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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.

Computer science. --- Health informatics. --- Data mining. --- Bioinformatics. --- Biomathematics. --- Computer Science. --- Health Informatics. --- Data Mining and Knowledge Discovery. --- Computational Biology/Bioinformatics. --- Genetics and Population Dynamics. --- Medicine --- Data processing. --- Computers in medicine --- Medical records --- Genetics --- Mathematics. --- Biology --- Embryology --- Mendel's law --- Adaptation (Biology) --- Breeding --- Chromosomes --- Heredity --- Mutation (Biology) --- Variation (Biology) --- Bio-informatics --- Biological informatics --- Information science --- Computational biology --- Systems biology --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- EHR systems --- EHR technology --- EHRs (Electronic health records) --- Electronic health records --- Electronic medical records --- EMR systems --- EMRs (Electronic medical records) --- Information storage and retrieval systems --- Data processing --- Medical care --- Health Workforce --- Mathematics --- Clinical informatics --- Health informatics --- Medical information science

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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.

Mathematics --- Biomathematics. Biometry. Biostatistics --- Genetics --- Molecular biology --- Human medicine --- Programming --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- datamining --- bio-informatica --- big data --- Bayesian statistics --- genetica --- medische informatica --- biometrie --- wiskunde --- gegevensanalyse --- KI (kunstmatige intelligentie) --- moleculaire biologie --- data acquisition