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Biblioteca

MARC Lista (tabellare)
Developing Medical Apps and mHealth Interventions [[electronic resource] ] : A Guide for Researchers, Physicians and Informaticians / / by Alan Davies, Julia Mueller
Developing Medical Apps and mHealth Interventions [[electronic resource] ] : A Guide for Researchers, Physicians and Informaticians / / by Alan Davies, Julia Mueller
Autore Davies Alan
Edizione [1st ed. 2020.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
Descrizione fisica 1 online resource (XXI, 380 p. 159 illus., 144 illus. in color.)
Disciplina 610.285
Collana Health Informatics
Soggetto topico Health informatics
Computer programming
Health Informatics
Programming Techniques
Informàtica mèdica
Aplicacions mòbils
Salut pública
Soggetto genere / forma Llibres electrònics
ISBN 3-030-47499-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Introduction to mHealth -- Project development methodologies, management and data modelling -- Designing an mHealth intervention -- Application development and testing -- Data collection, storage and security -- Feeding back information to patients and users with visualisations -- Usability testing and deployment -- Designing an mHealth evaluation -- Data analysis methods.
Record Nr. UNINA-9910411944703321
Davies Alan  
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Digital transformation and emerging technologies for fighting COVID-19 pandemic : innovative approaches / / edited by Aboul Ella Hassanien, Ashraf Darwish
Digital transformation and emerging technologies for fighting COVID-19 pandemic : innovative approaches / / edited by Aboul Ella Hassanien, Ashraf Darwish
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (304 pages)
Disciplina 006.3
Collana Studies in systems, decision and control (Online)
Soggetto topico Computational intelligence
Pandèmia de COVID-19, 2020-
Intel·ligència artificial en medicina
Informàtica mèdica
Dades massives
Soggetto genere / forma Llibres electrònics
ISBN 3-030-63307-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910483158603321
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Disruptive Innovation through Digital Transformation [[electronic resource] ] : Multi-Sided Platforms of E-Health in China / / by Xue Han, Yuanyuan Wu, Jie Zheng
Disruptive Innovation through Digital Transformation [[electronic resource] ] : Multi-Sided Platforms of E-Health in China / / by Xue Han, Yuanyuan Wu, Jie Zheng
Autore Han Xue
Edizione [1st ed. 2020.]
Pubbl/distr/stampa Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020
Descrizione fisica 1 online resource (XV, 108 p. 16 illus., 13 illus. in color.)
Disciplina 170.835
Soggetto topico Health care management
Health services administration
Information technology
Business—Data processing
Health Care Management
IT in Business
Indústria sanitària
Informàtica mèdica
Salut en línia
Soggetto genere / forma Llibres electrònics
ISBN 981-15-3944-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Chapter1. Introdcution -- Chapter2. Distinctive characterstics of Chinese healthcare industry -- Chapter3. Disruptive innovation in healthcare industry -- Chapter4. Governance of multi-sided platforms -- Chapter5. Multi-sided platforms(MSP) in China and their disruptive innovation -- Chapter6. Pair comparison of Chinese MSP with western MSPs -- Chapter7. Patient-participation in constructing the healthcare platform -- Chapter8. Conclusion and policy recommendations.
Record Nr. UNINA-9910411942603321
Han Xue  
Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Enhanced telemedicine and e-health : advanced loT enabled soft computing framework / / Gonçalo Marques [and three others] editors
Enhanced telemedicine and e-health : advanced loT enabled soft computing framework / / Gonçalo Marques [and three others] editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (359 pages)
Disciplina 610.285
Collana Studies in Fuzziness and Soft Computing
Soggetto topico Telecommunication in medicine
Telecomunicació en medicina
Informàtica mèdica
Soggetto genere / forma Llibres electrònics
ISBN 3-030-70111-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910483479503321
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Epidemiologic Research on Real-World Medical Data in Japan : Volume 1 / / edited by Naoki Nakashima
Epidemiologic Research on Real-World Medical Data in Japan : Volume 1 / / edited by Naoki Nakashima
Edizione [1st ed. 2022.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2022
Descrizione fisica 1 online resource (116 pages)
Disciplina 005.7
Collana SpringerBriefs for Data Scientists and Innovators
Soggetto topico Internal medicine
Business information services
Social sciences - Statistical methods
Medical care
Aging
Internal Medicine
IT in Business
Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy
Health Care
Ageing
Epidemiologia
Informàtica mèdica
Dades massives
Soggetto genere / forma Llibres electrònics
ISBN 9789811663765
9789811663758
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Part 1: Diagnosis Procedure Combination (DPC) -- Chapter 1. Development of a casemix system and its application in Japan -- Part 2: National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB) -- Chapter 2. The Present Status and Future Perspective of the National Database of Health Insurance Claim Information and Specified Medical Checkups of Japan (NDB) -- Chapter 3. Surveillances for Non-communicable Complex Diseases by National Databases of Health Insurance Claims and Specific Health Checkups of Japan -- Chapter 4. Powerful Analytics Platform for National-Scale Database of Health Care Insurance Claims -- Chapter 5. Panoramic view of diabetes from a standpoint of the NDB (National Database) -- Chapter 6. Nephrology Research in the NDB -- Part 3: Medical Information Database Network (MID-NET) -- Chapter 7. Drug safety assessment and the Japanese medical information database network (MID-NET®) -- Chapter 8. A Solution to the Problem of Data Quality in MID-NET -- Part 4: Disease Registration Cohort Study with EMR (SS-MIX2) -- Chapter 9. Health Information Standards -- Chapter 10. SS-MIX structured standardized storage -- Chapter 11. Japan Diabetes compREhensive database project based on an Advanced electronic Medical record System (J-DREAMS) -- Chapter 12. Japan Chronic Kidney Disease Database: J-CKD-DB -- Chapter 13. The Japan Medical Imaging Database (J-MID).
Record Nr. UNINA-9910574863703321
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Handbook of statistical bioinformatics / / Henry Horng-Shing Lu [and three others]
Handbook of statistical bioinformatics / / Henry Horng-Shing Lu [and three others]
Edizione [2nd ed.]
Pubbl/distr/stampa Berlin : , : Springer, , [2022]
Descrizione fisica 1 online resource (406 pages)
Disciplina 570.285
Collana Springer Handbooks of Computational Statistics
Soggetto topico Bioinformatics - Statistical methods
Bioinformatics
Bioinformàtica
Biologia computacional
Informàtica mèdica
Estadística matemàtica
Soggetto genere / forma Llibres electrònics
ISBN 3-662-65902-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Contents -- Part I Single-Cell Analysis -- Computational and Statistical Methods for Single-Cell RNA Sequencing Data -- 1 Introduction -- 2 Data Preprocessing -- 2.1 Reads Mapping -- 2.2 Cell Barcodes Demultiplexing -- 2.3 UMI Collapsing -- 2.4 Cell Barcodes Selection -- 2.5 Summary -- 3 Data Normalization and Visualization -- 3.1 Background -- 3.2 Global Scaling Normalization for UMI Data -- 3.3 Probabilistic Model-Based Normalization for UMI Data -- 3.4 Dimension Reduction and Cell Clustering -- 4 Dropout Imputation -- 4.1 Background -- 4.2 Cell-Cell Similarity-Based Imputation -- 4.3 Gene-Gene Similarity-Based Imputation -- 4.4 Gene-Gene and Cell-Cell Similarity-Based Imputation -- 4.5 Deep Neural Network-Based Imputation -- 4.6 G2S3 -- 4.7 Methods Evaluation and Comparison -- 5 Differential Expression Analysis -- 5.1 Background -- 5.2 DE Methods Ignoring Subject Effects -- 5.3 DE Methods Considering Subject Effects -- 5.4 iDESC -- 5.5 DE Methods Evaluation and Comparison -- 5.5.1 Type I Error Comparison -- 5.5.2 Statistical Power Comparison -- 6 Concluding Remarks -- References -- Pre-processing, Dimension Reduction, and Clustering for Single-Cell RNA-seq Data -- 1 Introduction -- 2 Pre-processing of scRNA-seq Data -- 2.1 Removal of Batch Effects -- 2.2 Quality Control and Feature Selection -- 3 Dimension Reduction and Clustering -- 3.1 Dimension Reduction -- 3.2 Clustering -- 4 Conclusion -- References -- Integrative Analyses of Single-Cell Multi-Omics Data: A Review from a Statistical Perspective -- 1 Multi-Omics Data Profiled on Different Cells -- 2 Multi-Omics Data Profiled on the Same Single Cells -- 3 Challenges and Future Perspectives -- References -- Approaches to Marker Gene Identification from Single-Cell RNA-Sequencing Data -- 1 Introduction.
2 Marker Gene Selection Relies on Identifying Differentially Expressed Genes -- 3 Methods for Marker Gene Selection -- 3.1 Highest Expressed, Highest Variable -- 4 Supervised Methods -- 4.1 COMET -- 4.2 scGeneFit -- 5 Unsupervised Methods -- 5.1 Seurat -- 5.2 SC3 -- 5.3 SCMarker -- 5.4 scTIM -- 5.5 RankCorr -- 6 Discussion -- References -- Model-Based Clustering of Single-Cell Omics Data -- 1 Introduction -- 2 Single-Cell Transcriptomic Data Clustering -- 2.1 Single-Cell Transcriptomic Data Structure -- 2.2 DIMM-SC -- 2.3 Real Data Example -- 3 Population-Scale Single-Cell Transcriptomic Data Clustering -- 3.1 Population-Scale Single-Cell Transcriptomic Data Structure -- 3.2 BAMM-SC -- 3.3 Real Data Example -- 4 Single-Cell Multi-omics Data Clustering -- 4.1 CITE-seq Data Structure -- 4.2 BREM-SC -- 4.3 Real Data Example -- 5 Concluding Remarks -- References -- Deep Learning Methods for Single-Cell Omics Data -- 1 Introduction -- 2 Factor-Model-Based Deep Learning Approaches -- 2.1 Regularization and Priors on the Latent Factors -- 2.1.1 Gaussian Prior and Variational Inference -- 2.1.2 Adjust for Batch Effects and Confounding Covariates: Identifiability -- 2.1.3 Adjust for Batch Effects and Confounding Covariates: Implementation -- 2.1.4 Model Cell Population Structure in the Latent Space -- 2.2 Distributional Assumptions on Observed Data -- 2.2.1 Model Observed Data from scRNA-seq -- 2.2.2 Model Observed Data from scATAC-seq -- 2.2.3 Model Observed Data from Single-Cell Multiomics Technologies -- 2.3 Post-training Statistical Analyses -- 2.3.1 Denoising -- 2.3.2 Visualization, Clustering, and Trajectory Analysis -- 2.3.3 Prediction -- 3 Deep Learning Methods for Dimension Reduction -- 3.1 Construct the Loss Function -- 3.2 Extra Penalties and Regularization -- 4 Discussion -- References -- Part II Network Analysis.
Probabilistic Graphical Models for Gene Regulatory Networks -- 1 Introduction -- 2 Probabilistic Graphical Models -- 2.1 Graphical Model Basics -- 2.2 Markov Networks -- 2.3 Bayesian Networks -- 3 Classic Graphical Models for Reconstructing GRNs -- 3.1 Frequentist Approach -- 3.2 Bayesian Approach -- 3.3 Graphical Models Incorporating Prior Knowledge -- 4 Testing in Graphical Models -- 4.1 Parametric Test -- 4.2 Non-parametric Test for Global Graph Structure -- 5 Conclusion -- References -- Additive Conditional Independence for Large and Complex Biological Structures -- 1 Additive Conditional Independence (ACI) -- 1.1 Additive Reproducing Kernel Hilbert Spaces and Relevant Linear Operators -- 2 Variable Selection via ACI -- 2.1 Nonparametric Variable Selection -- 2.2 Penalized Least-Square Estimation with RKHS Operators -- 2.3 Matrix Representation of Operators and Algorithm -- 2.4 Data Example -- 3 Graphical Modeling Through ACI -- 3.1 Nonparametric Graphical Models -- 3.2 The Additive Conditional Covariance and Partial Correlation Operators -- 3.3 Operator-Level Estimation and the Algorithm -- 3.4 Data Examples -- References -- Integration of Boolean and Bayesian Networks -- 1 Introduction -- 2 Methods -- 2.1 s-p-scores Associated with Networks, SPAN -- 2.2 Network Learning -- 3 Results -- 3.1 An Example -- 3.2 Real Example -- 3.3 Complex Example -- 4 Discussion -- References -- Computational Methods for Identifying MicroRNA-Gene Regulatory Modules -- 1 Introduction -- 2 Identifying MiRNA-Gene Modules by Integrating Heterogeneous Data Sources -- 2.1 Bipartite Graph-Based Methods -- 2.2 Nonnegative Matrix Factorization Methods -- 2.3 Statistical Modeling Approaches -- 3 Evaluating the Performance of MiRNA-Gene Module Identification Methods -- 4 Discussion -- 5 Conclusions -- References -- Causal Inference in Biostatistics -- 1 Introduction.
1.1 Causation and Association -- 1.2 Two Conceptual Frameworks: Causal Effect and Causal Discovery -- 2 Causal Effect -- 2.1 Approaches to Causal Inference -- 2.2 Randomized Clinical Trials -- 2.2.1 Perfect Randomized Trials -- 2.2.2 Randomized Trials with Missing Data -- 2.2.3 Randomized Trials with Post-treatment Variables -- 2.3 Observational Studies -- 2.3.1 Unconfounded Treatment Assignment Conditional on Measured Covariates -- 2.3.2 Unmeasured Cofounding -- 3 Some Current Research Topics -- 3.1 Heterogenous Treatment Effect and Precision Medicine -- 3.2 Integrating Data from Randomized Controlled Trials and Observational Studies -- 3.3 Multiple Treatments -- 4 Software Appendix -- References -- Bayesian Balance Mediation Analysis in Microbiome Studies -- 1 Introduction -- 2 Bayesian Balance Mediation Model -- 2.1 Bayesian Balance Mediation Model with a Binary Treatment -- 2.2 Direct and Mediation Effect and Estimation Based on Predictive Posterior Distribution -- 3 MCMC Sampling -- 3.1 MCMC Sampling -- 3.2 Conditional Distributions -- 4 Applications to Real Data -- 4.1 Mediation Analysis at the Phylum Level -- 4.2 Analysis at the Order Level -- 5 Simulation Studies -- 5.1 Data Generation -- 5.2 Simulation Result -- 6 Discussion -- References -- Part III Systems Biology -- Identifying Genetic Loci Associated with Complex Trait Variability -- 1 Introduction -- 2 The Concept of vQTL -- 3 Statistical Methods for vQTL Mapping -- 3.1 Classical Nonparametric Tests -- 3.2 Regression-Based Methods -- 3.3 Two-Stage Methods -- 3.4 Quantile Integral Linear Model (QUAIL) -- 3.5 Dispersion Effects -- 4 Applications of vQTL -- 4.1 Examples of vQTL -- 4.2 Screening vQTL for Candidate Loci Involved in GxE Interaction -- 4.3 Variance Polygenic Score -- 4.4 Other Applications and Future Directions -- References.
Cell Type-Specific Analysis for High-throughput Data -- 1 Introduction -- 2 Cell Type Composition Estimation -- 3 Cell Type-Specific Differential Analysis -- 4 Step-by-step Tutorial -- References -- Recent Development of Computational Methods in the Field of Epitranscriptomics -- 1 Introduction -- 2 MeRIP-seq and Other Technologies for RNA Modification Profiling -- 3 Methods to Analyze MeRIP-seq Data -- 3.1 Count-Based Methods for Simple Study Designs -- 3.2 Methods Compatible with Confounding Factors -- 3.3 A Guide for RNA Differential Methylation Analysis Using RADAR -- 4 Web Resources on m6A Epitranscriptome -- 4.1 Web Servers with m6A Site Prediction -- 4.2 m6A Epitranscriptome Database -- 5 Discussion -- References -- Estimation of Tumor Immune Signatures from Transcriptomics Data -- 1 Introduction -- 2 Regression-Based Deconvolution Algorithms -- 2.1 Linear Least Squares Regression -- 2.2 Support Vector Regression -- 2.3 Other Deconvolution Methods -- 3 Gene Set Enrichment-Based Methods and Other Gene-Based Algorithms -- 3.1 Gene Set Enrichment Analysis (GSEA) -- 3.2 Single-Sample GSEA (ssGSEA) -- 4 Benchmark Studies -- 5 Discussions -- References -- Cross-Linking Mass Spectrometry Data Analysis -- 1 Introduction -- 1.1 Peptide Identification Based on Mass Spectrometry -- 1.2 Cross-Linked Peptides Identification -- 1.2.1 Cross-Linker Selection -- 1.2.2 Chemical Reaction -- 1.2.3 Enzyme Digestion -- 1.2.4 Enrichment of Cross-Linked Peptides -- 1.2.5 LC-MS and MS2 Acquisition -- 1.2.6 Data Interpretation -- 1.2.7 Quality Control -- 1.2.8 Downstream Applications -- 2 Non-cleavable Cross-Linking Methods -- 3 Cleavable Cross-Linking Methods -- 4 Time-Complexity Comparison Between Non-cleavable Methods and Cleavable Methods -- 5 False Discovery Rate in CL-MS -- 5.1 Target-Decoy Approach in Linear Peptides Identification.
5.2 TDA in Cross-Linked Peptides Identification.
Record Nr. UNINA-9910634054103321
Berlin : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Handbook of statistical bioinformatics / / Henry Horng-Shing Lu [and three others]
Handbook of statistical bioinformatics / / Henry Horng-Shing Lu [and three others]
Edizione [2nd ed.]
Pubbl/distr/stampa Berlin : , : Springer, , [2022]
Descrizione fisica 1 online resource (406 pages)
Disciplina 570.285
Collana Springer Handbooks of Computational Statistics
Soggetto topico Bioinformatics - Statistical methods
Bioinformatics
Bioinformàtica
Biologia computacional
Informàtica mèdica
Estadística matemàtica
Soggetto genere / forma Llibres electrònics
ISBN 3-662-65902-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Contents -- Part I Single-Cell Analysis -- Computational and Statistical Methods for Single-Cell RNA Sequencing Data -- 1 Introduction -- 2 Data Preprocessing -- 2.1 Reads Mapping -- 2.2 Cell Barcodes Demultiplexing -- 2.3 UMI Collapsing -- 2.4 Cell Barcodes Selection -- 2.5 Summary -- 3 Data Normalization and Visualization -- 3.1 Background -- 3.2 Global Scaling Normalization for UMI Data -- 3.3 Probabilistic Model-Based Normalization for UMI Data -- 3.4 Dimension Reduction and Cell Clustering -- 4 Dropout Imputation -- 4.1 Background -- 4.2 Cell-Cell Similarity-Based Imputation -- 4.3 Gene-Gene Similarity-Based Imputation -- 4.4 Gene-Gene and Cell-Cell Similarity-Based Imputation -- 4.5 Deep Neural Network-Based Imputation -- 4.6 G2S3 -- 4.7 Methods Evaluation and Comparison -- 5 Differential Expression Analysis -- 5.1 Background -- 5.2 DE Methods Ignoring Subject Effects -- 5.3 DE Methods Considering Subject Effects -- 5.4 iDESC -- 5.5 DE Methods Evaluation and Comparison -- 5.5.1 Type I Error Comparison -- 5.5.2 Statistical Power Comparison -- 6 Concluding Remarks -- References -- Pre-processing, Dimension Reduction, and Clustering for Single-Cell RNA-seq Data -- 1 Introduction -- 2 Pre-processing of scRNA-seq Data -- 2.1 Removal of Batch Effects -- 2.2 Quality Control and Feature Selection -- 3 Dimension Reduction and Clustering -- 3.1 Dimension Reduction -- 3.2 Clustering -- 4 Conclusion -- References -- Integrative Analyses of Single-Cell Multi-Omics Data: A Review from a Statistical Perspective -- 1 Multi-Omics Data Profiled on Different Cells -- 2 Multi-Omics Data Profiled on the Same Single Cells -- 3 Challenges and Future Perspectives -- References -- Approaches to Marker Gene Identification from Single-Cell RNA-Sequencing Data -- 1 Introduction.
2 Marker Gene Selection Relies on Identifying Differentially Expressed Genes -- 3 Methods for Marker Gene Selection -- 3.1 Highest Expressed, Highest Variable -- 4 Supervised Methods -- 4.1 COMET -- 4.2 scGeneFit -- 5 Unsupervised Methods -- 5.1 Seurat -- 5.2 SC3 -- 5.3 SCMarker -- 5.4 scTIM -- 5.5 RankCorr -- 6 Discussion -- References -- Model-Based Clustering of Single-Cell Omics Data -- 1 Introduction -- 2 Single-Cell Transcriptomic Data Clustering -- 2.1 Single-Cell Transcriptomic Data Structure -- 2.2 DIMM-SC -- 2.3 Real Data Example -- 3 Population-Scale Single-Cell Transcriptomic Data Clustering -- 3.1 Population-Scale Single-Cell Transcriptomic Data Structure -- 3.2 BAMM-SC -- 3.3 Real Data Example -- 4 Single-Cell Multi-omics Data Clustering -- 4.1 CITE-seq Data Structure -- 4.2 BREM-SC -- 4.3 Real Data Example -- 5 Concluding Remarks -- References -- Deep Learning Methods for Single-Cell Omics Data -- 1 Introduction -- 2 Factor-Model-Based Deep Learning Approaches -- 2.1 Regularization and Priors on the Latent Factors -- 2.1.1 Gaussian Prior and Variational Inference -- 2.1.2 Adjust for Batch Effects and Confounding Covariates: Identifiability -- 2.1.3 Adjust for Batch Effects and Confounding Covariates: Implementation -- 2.1.4 Model Cell Population Structure in the Latent Space -- 2.2 Distributional Assumptions on Observed Data -- 2.2.1 Model Observed Data from scRNA-seq -- 2.2.2 Model Observed Data from scATAC-seq -- 2.2.3 Model Observed Data from Single-Cell Multiomics Technologies -- 2.3 Post-training Statistical Analyses -- 2.3.1 Denoising -- 2.3.2 Visualization, Clustering, and Trajectory Analysis -- 2.3.3 Prediction -- 3 Deep Learning Methods for Dimension Reduction -- 3.1 Construct the Loss Function -- 3.2 Extra Penalties and Regularization -- 4 Discussion -- References -- Part II Network Analysis.
Probabilistic Graphical Models for Gene Regulatory Networks -- 1 Introduction -- 2 Probabilistic Graphical Models -- 2.1 Graphical Model Basics -- 2.2 Markov Networks -- 2.3 Bayesian Networks -- 3 Classic Graphical Models for Reconstructing GRNs -- 3.1 Frequentist Approach -- 3.2 Bayesian Approach -- 3.3 Graphical Models Incorporating Prior Knowledge -- 4 Testing in Graphical Models -- 4.1 Parametric Test -- 4.2 Non-parametric Test for Global Graph Structure -- 5 Conclusion -- References -- Additive Conditional Independence for Large and Complex Biological Structures -- 1 Additive Conditional Independence (ACI) -- 1.1 Additive Reproducing Kernel Hilbert Spaces and Relevant Linear Operators -- 2 Variable Selection via ACI -- 2.1 Nonparametric Variable Selection -- 2.2 Penalized Least-Square Estimation with RKHS Operators -- 2.3 Matrix Representation of Operators and Algorithm -- 2.4 Data Example -- 3 Graphical Modeling Through ACI -- 3.1 Nonparametric Graphical Models -- 3.2 The Additive Conditional Covariance and Partial Correlation Operators -- 3.3 Operator-Level Estimation and the Algorithm -- 3.4 Data Examples -- References -- Integration of Boolean and Bayesian Networks -- 1 Introduction -- 2 Methods -- 2.1 s-p-scores Associated with Networks, SPAN -- 2.2 Network Learning -- 3 Results -- 3.1 An Example -- 3.2 Real Example -- 3.3 Complex Example -- 4 Discussion -- References -- Computational Methods for Identifying MicroRNA-Gene Regulatory Modules -- 1 Introduction -- 2 Identifying MiRNA-Gene Modules by Integrating Heterogeneous Data Sources -- 2.1 Bipartite Graph-Based Methods -- 2.2 Nonnegative Matrix Factorization Methods -- 2.3 Statistical Modeling Approaches -- 3 Evaluating the Performance of MiRNA-Gene Module Identification Methods -- 4 Discussion -- 5 Conclusions -- References -- Causal Inference in Biostatistics -- 1 Introduction.
1.1 Causation and Association -- 1.2 Two Conceptual Frameworks: Causal Effect and Causal Discovery -- 2 Causal Effect -- 2.1 Approaches to Causal Inference -- 2.2 Randomized Clinical Trials -- 2.2.1 Perfect Randomized Trials -- 2.2.2 Randomized Trials with Missing Data -- 2.2.3 Randomized Trials with Post-treatment Variables -- 2.3 Observational Studies -- 2.3.1 Unconfounded Treatment Assignment Conditional on Measured Covariates -- 2.3.2 Unmeasured Cofounding -- 3 Some Current Research Topics -- 3.1 Heterogenous Treatment Effect and Precision Medicine -- 3.2 Integrating Data from Randomized Controlled Trials and Observational Studies -- 3.3 Multiple Treatments -- 4 Software Appendix -- References -- Bayesian Balance Mediation Analysis in Microbiome Studies -- 1 Introduction -- 2 Bayesian Balance Mediation Model -- 2.1 Bayesian Balance Mediation Model with a Binary Treatment -- 2.2 Direct and Mediation Effect and Estimation Based on Predictive Posterior Distribution -- 3 MCMC Sampling -- 3.1 MCMC Sampling -- 3.2 Conditional Distributions -- 4 Applications to Real Data -- 4.1 Mediation Analysis at the Phylum Level -- 4.2 Analysis at the Order Level -- 5 Simulation Studies -- 5.1 Data Generation -- 5.2 Simulation Result -- 6 Discussion -- References -- Part III Systems Biology -- Identifying Genetic Loci Associated with Complex Trait Variability -- 1 Introduction -- 2 The Concept of vQTL -- 3 Statistical Methods for vQTL Mapping -- 3.1 Classical Nonparametric Tests -- 3.2 Regression-Based Methods -- 3.3 Two-Stage Methods -- 3.4 Quantile Integral Linear Model (QUAIL) -- 3.5 Dispersion Effects -- 4 Applications of vQTL -- 4.1 Examples of vQTL -- 4.2 Screening vQTL for Candidate Loci Involved in GxE Interaction -- 4.3 Variance Polygenic Score -- 4.4 Other Applications and Future Directions -- References.
Cell Type-Specific Analysis for High-throughput Data -- 1 Introduction -- 2 Cell Type Composition Estimation -- 3 Cell Type-Specific Differential Analysis -- 4 Step-by-step Tutorial -- References -- Recent Development of Computational Methods in the Field of Epitranscriptomics -- 1 Introduction -- 2 MeRIP-seq and Other Technologies for RNA Modification Profiling -- 3 Methods to Analyze MeRIP-seq Data -- 3.1 Count-Based Methods for Simple Study Designs -- 3.2 Methods Compatible with Confounding Factors -- 3.3 A Guide for RNA Differential Methylation Analysis Using RADAR -- 4 Web Resources on m6A Epitranscriptome -- 4.1 Web Servers with m6A Site Prediction -- 4.2 m6A Epitranscriptome Database -- 5 Discussion -- References -- Estimation of Tumor Immune Signatures from Transcriptomics Data -- 1 Introduction -- 2 Regression-Based Deconvolution Algorithms -- 2.1 Linear Least Squares Regression -- 2.2 Support Vector Regression -- 2.3 Other Deconvolution Methods -- 3 Gene Set Enrichment-Based Methods and Other Gene-Based Algorithms -- 3.1 Gene Set Enrichment Analysis (GSEA) -- 3.2 Single-Sample GSEA (ssGSEA) -- 4 Benchmark Studies -- 5 Discussions -- References -- Cross-Linking Mass Spectrometry Data Analysis -- 1 Introduction -- 1.1 Peptide Identification Based on Mass Spectrometry -- 1.2 Cross-Linked Peptides Identification -- 1.2.1 Cross-Linker Selection -- 1.2.2 Chemical Reaction -- 1.2.3 Enzyme Digestion -- 1.2.4 Enrichment of Cross-Linked Peptides -- 1.2.5 LC-MS and MS2 Acquisition -- 1.2.6 Data Interpretation -- 1.2.7 Quality Control -- 1.2.8 Downstream Applications -- 2 Non-cleavable Cross-Linking Methods -- 3 Cleavable Cross-Linking Methods -- 4 Time-Complexity Comparison Between Non-cleavable Methods and Cleavable Methods -- 5 False Discovery Rate in CL-MS -- 5.1 Target-Decoy Approach in Linear Peptides Identification.
5.2 TDA in Cross-Linked Peptides Identification.
Record Nr. UNISA-996503551803316
Berlin : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Health information science and systems
Health information science and systems
Pubbl/distr/stampa London, : BioMed Central, 2013-
Descrizione fisica 1 online resource
Soggetto topico Medical informatics
Medicine - Data processing
Medical Informatics
Informàtica mèdica
Soggetto genere / forma Periodical
Fulltext
Internet Resources.
Periodicals.
Revistes electròniques.
Soggetto non controllato Medical & Biomedical Informatics
ISSN 2047-2501
Formato Materiale a stampa
Livello bibliografico Periodico
Lingua di pubblicazione eng
Record Nr. UNISA-996200821703316
London, : BioMed Central, 2013-
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Health information science and systems
Health information science and systems
Pubbl/distr/stampa London, : BioMed Central, 2013-
Descrizione fisica 1 online resource
Soggetto topico Medical informatics
Medicine - Data processing
Medical Informatics
Informàtica mèdica
Soggetto genere / forma Periodical
Fulltext
Internet Resources.
Periodicals.
Revistes electròniques.
Soggetto non controllato Medical & Biomedical Informatics
ISSN 2047-2501
Formato Materiale a stampa
Livello bibliografico Periodico
Lingua di pubblicazione eng
Record Nr. UNINA-9910141585603321
London, : BioMed Central, 2013-
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Management of Orbito-zygomaticomaxillary Fractures [[electronic resource] /] / by Hisham Marwan, Yoh Sawatari, Michael Peleg
Management of Orbito-zygomaticomaxillary Fractures [[electronic resource] /] / by Hisham Marwan, Yoh Sawatari, Michael Peleg
Autore Marwan Hisham
Edizione [1st ed. 2020.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
Descrizione fisica 1 online resource (VIII, 112 p. 102 illus., 93 illus. in color.)
Disciplina 617.52059
Soggetto topico Oral surgery
Maxillofacial surgery
Fractures
Cirurgia maxil·lofacial
Cirurgia oral
Visualització tridimensional
Informàtica mèdica
Oral and Maxillofacial Surgery
Soggetto genere / forma Llibres electrònics
ISBN 3-030-42645-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Introduction and surgical Anatomy of Orbito-Zygomaticomaxillary Fractures -- Preoperative Assessment of Orbito-Zygomaticomaxillary Fractures -- Preoperative surgical planning of Orbito-Zygomaticomaxillary Fractures -- Surgical Access to Orbito-Zygomaticomaxillary Fractures -- Fixation Techniques for Orbito-Zygomaticomaxillary Fractures -- Soft tissue management for Orbito-Zygomaticomaxillary Fractures -- Intraoperative Assessment of Orbito-Zygomaticomaxillary Fractures -- Postoperative Assessment of Orbito-Zygomaticomaxillary Fractures -- Complications of Orbito-Zygomaticomaxillary Fractures -- New advances in the planning and management of Orbito-Zygomaticomaxillary Fractures -- Delayed management of the orbito-zygomaticomaxillary fracture -- Management of post traumatic orbito-zygomaticomaxillary deformities. .
Record Nr. UNINA-9910411941703321
Marwan Hisham  
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
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