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000799791 019__ $$a1003517276
000799791 020__ $$a9783319449814$$q(electronic book)
000799791 020__ $$a3319449818$$q(electronic book)
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000799791 050_4 $$aR858
000799791 08204 $$a610.285$$223
000799791 24500 $$aHealth informatics data analysis :$$bmethods and examples /$$cDong Xu, May D. Wang, Fengfeng Zhou, Yunpeng Cai, editors.
000799791 264_1 $$aCham, Switzerland :$$bSpringer,$$c2017.
000799791 300__ $$a1 online resource.
000799791 336__ $$atext$$btxt$$2rdacontent
000799791 337__ $$acomputer$$bc$$2rdamedia
000799791 338__ $$aonline resource$$bcr$$2rdacarrier
000799791 4901_ $$aHealth information science
000799791 504__ $$aIncludes bibliographical references.
000799791 5050_ $$aPreface; Contents; 1 Global Nonlinear Fitness Function for Protein Structures; Abstract; Introduction; Theory and Models; Modeling Protein Fitness Function; Two Geometric Views of Linear Protein Potentials; Optimal Linear Fitness Function; Relation to Support Vector Machines; Nonlinear Scoring Function; Optimal Nonlinear Fitness Function; Rectangle Kernel and Reduced Support Vector Machine (RSVM); Smooth Newton Method; Computational Procedures; Protein Data; Contact Maps and Sequence Decoys; Learning Linear Fitness Function; Learning Full Nonlinear Fitness Function
000799791 5058_ $$aLearning Simplified Nonlinear Fitness FunctionResults; Linear Fitness Functions; Full Nonlinear Fitness Function; Results of Simplified Nonlinear Fitness Function; Discussion; References; 2 Computational Methods for Mass Spectrometry Imaging: Challenges, Progress, and Opportunities; Abstract; Introduction; Challenges; Challenge 1: Integration of MSI Data with Complementary Imaging Modalities; Challenge 2: Movement Toward MSI from Three-Dimensional Samples; Challenge 3: Reproducibility, Data Standardization, and Community Resources; Current Techniques in MSI Analysis; Case Study; Conclusion
000799791 5058_ $$aAcknowledgementsReferences; 3 Identification and Functional Annotation of LncRNAs in Human Disease; Abstract; Background; Current Bioinformatics Methods; Identify Associated lncRNAs in Human Diseases; By Microarray; By RNA-seq; Annotated the Functions of Associated lncRNAs in Human Diseases Based on Co-expression Network; Further Analysis of LncRNAs After Identification and Functional Annotation; Challenges and Current Problems; Example; Identification of Differentially Expressed lncRNAs in Gastric Cancer; Conclusion; References; 4 Metabolomics Characterization of Human Diseases; Abstract
000799791 5058_ $$aBackgroundChallenges; Current Techniques; Example One-Pathway Analysis To Understand the Change of Pattern in Metabolomics Profiles; Example Two-Development of a Classification Model Using Metabolite Biomarkers for Discriminating Disease Samples from Controls; Conclusions; References; 5 Metagenomics for Monitoring Environmental Biodiversity: Challenges, Progress, and Opportunities; Abstract; Introduction; Sampling and Experimental Design; Metagenomic Sequencing and Preprocessing; Metagenomic Data Analyses; Platforms; Example: Bacteria 16S RRNA Metagenomics Pipeline; Conclusion; References
000799791 5058_ $$a6 Clinical Assessment of Disease Risk Factors Using SNP Data and Bayesian MethodsAbstract; Promise and Complexity of Personalized Medicine; Whole-Genome Association Studies; Beyond Single-Locus Analysis; Modern Bioinformatics Approaches; Bayesian Data Analysis Methods; Overview of Bayesian Data Analysis; Overview of Bayesian Variable Partition; Epistasis Analysis Methods; Incorporating Block-Type Genome Structure; Detailed Interaction Partition Structure Determination; Bayesian Graph Models and Networks; Clinical Applications of Bayesian Methodology; Conclusions and Future Prospects
000799791 506__ $$aAccess limited to authorized users.
000799791 520__ $$aThis book provides a comprehensive overview of different biomedical data types, including both clinical and genomic data. Thorough explanations enable readers to explore key topics ranging from electrocardiograms to Big Data health mining and EEG analysis techniques. Each chapter offers a summary of the field and a sample analysis. Also covered are telehealth infrastructure, healthcare information association rules, methods for mass spectrometry imaging, environmental biodiversity, and the global nonlinear fitness function for protein structures. Diseases are addressed in chapters on functional annotation of lncRNAs in human disease, metabolomics characterization of human diseases, disease risk factors using SNP data and Bayesian methods, and imaging informatics for diagnostic imaging marker selection. With the exploding accumulation of Electronic Health Records (EHRs), there is an urgent need for computer-aided analysis of heterogeneous biomedical datasets. Biomedical data is notorious for its diversified scales, dimensions, and volumes, and requires interdisciplinary technologies for visual illustration and digital characterization. Various computer programs and servers have been developed for these purposes by both theoreticians and engineers. This book is an essential reference for investigating the tools available for analyzing heterogeneous biomedical data. It is designed for professionals, researchers, and practitioners in biomedical engineering, diagnostics, medical electronics, and related industries.
000799791 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed September 19, 2017).
000799791 650_0 $$aMedicine$$xData processing.
000799791 7001_ $$aXu, Dong,$$d1965-$$eeditor.
000799791 7001_ $$aWang, May D.,$$eeditor.
000799791 7001_ $$aZhou, Fengfeng,$$eeditor.
000799791 7001_ $$aCai, Yunpeng,$$eeditor.
000799791 77608 $$iPrint version:$$z3319449796$$z9783319449791$$w(OCoLC)953843019
000799791 830_0 $$aHealth information science.
000799791 852__ $$bebk
000799791 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-44981-4$$zOnline Access$$91397441.1
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000799791 982__ $$aEbook
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