Extended abstracts Fall 2015 : Biomedical Big Data ; Statistics for Low Dose Radiation Research / Elizabeth A. Ainsbury, M. Luz Calle, Elisabeth Cardis, Jochen Einbeck, Guadalupe Gómez, Pere Puig, editors.

This two-part volume gathers extended conference abstracts corresponding to selected talks from the "Biostatnet workshop on Biomedical (Big) Data" and from the "DoReMi LD-RadStats: Workshop for statisticians interested in contributing to EU low dose radiation research", which wer...

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Online Access: Full Text (via Springer)
Other Authors: Ainsbury, Elizabeth A. (Editor), Calle, M. Luz (Editor), Cardis, Elisabeth Marcelle (Editor), Einbeck, Jochen (Editor), Gómez, Guadalupe (Editor), Puig i Casado, Pere (Editor)
Format: eBook
Language:English
Published: Cham, Switzerland : Birkhäuser, 2017.
Series:Trends in mathematics ; v. 7.
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MARC

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505 0 |a Part I Biomedical Big Data; Extreme Observations in Biomedical Data; 1 Introduction; 2 Methods; 3 Application to Data in Autism Multiplex Families; 4 Application to Gene Expression Data in Cancer; References; An Ordinal Joint Model for Breast Cancer; 1 Introduction; 2 A Bayesian Joint Model for Ordinal Longitudinal and Left Truncated Survival Data; 3 Breast Cancer and Mammographic Breast Density; References; Sample Size Impact on the Categorisation of Continuous Variables in Clinical Prediction; 1 Motivation; 2 Methods. 
505 8 |a 2.1 Categorisation Proposal Based on GAM with P-Spline Smoothers; 2.2 Optimal Categorisation Based on the Maximisation of the AUC; 3 Simulation Study; 3.1 Scenarios and Set Up; 3.2 Results; 4 Conclusions; References; Integrative Analysis of Transcriptomics and Proteomics Data for the Characterization of Brain Tissue After Ischemic Stroke; 1 Introduction and Objectives; 2 Methods; 3 Results; 4 Conclusions; References; Applying INAR-Hidden Markov Chains in the Analysis of Under-Reported Data; 1 Introduction; 2 The Model; 2.1 Parameter Estimation; 2.2 Reconstruction of the Underlying Process. 
505 8 |a 2.3 Model Selection and Goodness of Fit; 3 Example of Application; References; Joint Modelling for Flexible Multivariate Longitudinal and Survival Data: Application in Orthotopic Liver Transplantation; 1 Introduction; 2 Orthotopic Liver Transplantation Data; 3 Two-Stage Model Based Proposal; 3.1 Stage 1: Flexible Multivariate Longitudinal Data; 3.2 Stage 2: Survival Model; 4 Conclusions; References; A Multi-state Model for the Progression to Osteopenia and Osteoporosis Among HIV-Infected Patients; 1 Motivation; 2 Multi-state Model; 2.1 Notation; 2.2 Estimation Method; 3 Results. 
505 8 |a 3.1 Descriptive Analysis; 3.2 Estimated Transition Probabilities; 4 Discussion; References; Statistical Challenges for Human Microbiome Analysis; 1 Introduction; 2 Methods; 3 Results; 4 Conclusions; References; Integrative Analysis to Select Genes Regulated by Methylation in a Cancer Colon Study; 1 Introduction and Objectives; 2 Methods for L-Pattern Selection; 2.1 Gene Selection Based on Conditional Mutual Information; 2.2 Gene Selection Based on Spline Regression; 3 Results and Application: Selecting L-Shaped Genes from a Genome-Wide Analysis of Colorectal Cancer. 
505 8 |a 3.1 Results Using the Conditional Mutual Information Approach; 3.2 Results Using Splines Regression to Select Genes; 4 Discussion and Conclusions; References; Topological Pathway Enrichment Analysis of Gene Expression in High Grade Serous Ovarian Cancer Reveals Tumor-Stoma Cross-Talk; 1 Introduction; 2 Methods; 3 Results; 4 Discussion; 5 Conclusion; References; Part II Statistics for Low Dose Radiation Research; Biological Dosimetry, Statistical Challenges: Biological Dosimetry After High-Dose Exposures to Ionizing Radiation; References. 
504 |a Includes bibliographical references at the end of each chapters. 
520 |a This two-part volume gathers extended conference abstracts corresponding to selected talks from the "Biostatnet workshop on Biomedical (Big) Data" and from the "DoReMi LD-RadStats: Workshop for statisticians interested in contributing to EU low dose radiation research", which were held at the Centre de Recerca Matemàtica (CRM) in Barcelona from November 26th to 27th, 2015, and at the Institut de Salut Global ISGlobal (former CREAL) from October 26th to 28th, 2015, respectively. Most of the contributions are brief articles, presenting preliminary new results not yet published in regular research journals. The first part is devoted to the challenges of analyzing so called "Biomedical Big Data", tremendous amounts of biomedical and health data that are generated every day due to the use of recent technological advances such as massive genomic sequencing, electronic health records or high-resolution medical imaging, among others. The analysis of this information poses significant challenges for researchers in the fields of biostatistics, bioinformatics, and signal processing. Furthermore, other relevant challenges in biostatistical research, not necessarily involving big data, are also discussed. In turn, the second part is dedicated to low dose radiation research, where there is a need to fully understand and characterize potential sources of uncertainty before they can be reduced. Further, the book demonstrates why formal uncertainty analysis has the potential to provide a common platform for multidisciplinary research in this field. This book is intended for established researchers, as well as for PhD and postdoctoral students who want to learn more about the latest advances in these highly active areas of research. 
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