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Author: Yichuan Zhao
Publisher: Springer
ISBN: 3319993895
Category : Mathematics
Languages : en
Pages : 473
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Book Description
This book is comprised of presentations delivered at the 5th Workshop on Biostatistics and Bioinformatics held in Atlanta on May 5-7, 2017. Featuring twenty-two selected papers from the workshop, this book showcases the most current advances in the field, presenting new methods, theories, and case applications at the frontiers of biostatistics, bioinformatics, and interdisciplinary areas. Biostatistics and bioinformatics have been playing a key role in statistics and other scientific research fields in recent years. The goal of the 5th Workshop on Biostatistics and Bioinformatics was to stimulate research, foster interaction among researchers in field, and offer opportunities for learning and facilitating research collaborations in the era of big data. The resulting volume offers timely insights for researchers, students, and industry practitioners.
Author: Yichuan Zhao
Publisher: Springer
ISBN: 3319993895
Category : Mathematics
Languages : en
Pages : 473
Get Book Here
Book Description
This book is comprised of presentations delivered at the 5th Workshop on Biostatistics and Bioinformatics held in Atlanta on May 5-7, 2017. Featuring twenty-two selected papers from the workshop, this book showcases the most current advances in the field, presenting new methods, theories, and case applications at the frontiers of biostatistics, bioinformatics, and interdisciplinary areas. Biostatistics and bioinformatics have been playing a key role in statistics and other scientific research fields in recent years. The goal of the 5th Workshop on Biostatistics and Bioinformatics was to stimulate research, foster interaction among researchers in field, and offer opportunities for learning and facilitating research collaborations in the era of big data. The resulting volume offers timely insights for researchers, students, and industry practitioners.
Author: Bourama Toni
Publisher: Springer
ISBN: 3319077554
Category : Mathematics
Languages : en
Pages : 405
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Book Description
This highly multidisciplinary volume contains contributions from leading researchers in STEAM-H disciplines (Science, Technology, Engineering, Agriculture, Mathematics and Health). The volume explores new frontiers in multidisciplinary research, including: the mathematics of cardiac arrhythmia; brain research on working memory; penalized ordinal regression to classify melanoma skin samples; forecasting of time series data; dynamics of niche models; analysis of chemical moieties as anticancer agents; study of gene locus control regions; qualitative mathematical modelling; convex quadrics and group circle systems; remanufacturing planning and control; complexity reduction of functional differential equations; computation of viscous interfacial motion; and differentiation in human pluripotent stem cells. An extension of a seminar series at Virginia State University, the collection is intended to foster student interest and participation in interdisciplinary research and to stimulate new research. The content will be of interest to a broad spectrum of scientists, mathematicians and research students working in interdisciplinary fields including the biosciences, mathematics, engineering, neurosciences and behavioral sciences.
Author: Plamen Ch. Ivanov
Publisher: Frontiers Media SA
ISBN: 2889714357
Category : Science
Languages : en
Pages : 842
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Book Description
Author: Somnath Datta
Publisher: Springer
ISBN: 9783319379050
Category : Medical
Languages : en
Pages : 0
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Book Description
Next Generation Sequencing (NGS) is the latest high throughput technology to revolutionize genomic research. NGS generates massive genomic datasets that play a key role in the big data phenomenon that surrounds us today. To extract signals from high-dimensional NGS data and make valid statistical inferences and predictions, novel data analytic and statistical techniques are needed. This book contains 20 chapters written by prominent statisticians working with NGS data. The topics range from basic preprocessing and analysis with NGS data to more complex genomic applications such as copy number variation and isoform expression detection. Research statisticians who want to learn about this growing and exciting area will find this book useful. In addition, many chapters from this book could be included in graduate-level classes in statistical bioinformatics for training future biostatisticians who will be expected to deal with genomic data in basic biomedical research, genomic clinical trials and personalized medicine. About the editors: Somnath Datta is Professor and Vice Chair of Bioinformatics and Biostatistics at the University of Louisville. He is Fellow of the American Statistical Association, Fellow of the Institute of Mathematical Statistics and Elected Member of the International Statistical Institute. He has contributed to numerous research areas in Statistics, Biostatistics and Bioinformatics. Dan Nettleton is Professor and Laurence H. Baker Endowed Chair of Biological Statistics in the Department of Statistics at Iowa State University. He is Fellow of the American Statistical Association and has published research on a variety of topics in statistics, biology and bioinformatics.
Author: Somnath Datta
Publisher: Springer Nature
ISBN: 3030733513
Category : Medical
Languages : en
Pages : 349
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Book Description
Microbiome research has focused on microorganisms that live within the human body and their effects on health. During the last few years, the quantification of microbiome composition in different environments has been facilitated by the advent of high throughput sequencing technologies. The statistical challenges include computational difficulties due to the high volume of data; normalization and quantification of metabolic abundances, relative taxa and bacterial genes; high-dimensionality; multivariate analysis; the inherently compositional nature of the data; and the proper utilization of complementary phylogenetic information. This has resulted in an explosion of statistical approaches aimed at tackling the unique opportunities and challenges presented by microbiome data. This book provides a comprehensive overview of the state of the art in statistical and informatics technologies for microbiome research. In addition to reviewing demonstrably successful cutting-edge methods, particular emphasis is placed on examples in R that rely on available statistical packages for microbiome data. With its wide-ranging approach, the book benefits not only trained statisticians in academia and industry involved in microbiome research, but also other scientists working in microbiomics and in related fields.
Author:
Publisher: DIANE Publishing
ISBN: 1437906869
Category :
Languages : en
Pages : 26
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Book Description
Author: Ding-Geng Chen
Publisher: Springer
ISBN: 3319694162
Category : Mathematics
Languages : en
Pages : 355
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Book Description
This book is comprised of the presentations delivered at the 25th ICSA Applied Statistics Symposium held at the Hyatt Regency Atlanta, on June 12-15, 2016. This symposium attracted more than 700 statisticians and data scientists working in academia, government, and industry from all over the world. The theme of this conference was the “Challenge of Big Data and Applications of Statistics,” in recognition of the advent of big data era, and the symposium offered opportunities for learning, receiving inspirations from old research ideas and for developing new ones, and for promoting further research collaborations in the data sciences. The invited contributions addressed rich topics closely related to big data analysis in the data sciences, reflecting recent advances and major challenges in statistics, business statistics, and biostatistics. Subsequently, the six editors selected 19 high-quality presentations and invited the speakers to prepare full chapters for this book, which showcases new methods in statistics and data sciences, emerging theories, and case applications from statistics, data science and interdisciplinary fields. The topics covered in the book are timely and have great impact on data sciences, identifying important directions for future research, promoting advanced statistical methods in big data science, and facilitating future collaborations across disciplines and between theory and practice.
Author: Shigeyuki Matsui
Publisher: Springer
ISBN: 981100126X
Category : Medical
Languages : en
Pages : 439
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Book Description
This book presents the state of the art of biostatistical methods and their applications in clinical oncology. Many methodologies established today in biostatistics have been brought about through its applications to the design and analysis of oncology clinical studies. This field of oncology, now in the midst of evolution owing to rapid advances in biotechnologies and cancer genomics, is becoming one of the most promising disease fields in the shift toward personalized medicine. Modern developments of diagnosis and therapeutics of cancer have also been continuously fueled by recent progress in establishing the infrastructure for conducting more complex, large-scale clinical trials and observational studies. The field of cancer clinical studies therefore will continue to provide many new statistical challenges that warrant further progress in the methodology and practice of biostatistics. This book provides a systematic coverage of various stages of cancer clinical studies. Topics from modern cancer clinical trials include phase I clinical trials for combination therapies, exploratory phase II trials with multiple endpoints/treatments, and confirmative biomarker-based phase III trials with interim monitoring and adaptation. It also covers important areas of cancer screening, prognostic analysis, and the analysis of large-scale molecular data in the era of big data.
Author: Yichuan Zhao
Publisher: Springer Nature
ISBN: 3030334163
Category : Medical
Languages : en
Pages : 495
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Book Description
This edited collection discusses the emerging topics in statistical modeling for biomedical research. Leading experts in the frontiers of biostatistics and biomedical research discuss the statistical procedures, useful methods, and their novel applications in biostatistics research. Interdisciplinary in scope, the volume as a whole reflects the latest advances in statistical modeling in biomedical research, identifies impactful new directions, and seeks to drive the field forward. It also fosters the interaction of scholars in the arena, offering great opportunities to stimulate further collaborations. This book will appeal to industry data scientists and statisticians, researchers, and graduate students in biostatistics and biomedical science. It covers topics in: Next generation sequence data analysis Deep learning, precision medicine, and their applications Large scale data analysis and its applications Biomedical research and modeling Survival analysis with complex data structure and its applications.
Author: Ming-Hui Chen
Publisher: Springer Science & Business Media
ISBN: 1441969446
Category : Mathematics
Languages : en
Pages : 631
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Book Description
Research in Bayesian analysis and statistical decision theory is rapidly expanding and diversifying, making it increasingly more difficult for any single researcher to stay up to date on all current research frontiers. This book provides a review of current research challenges and opportunities. While the book can not exhaustively cover all current research areas, it does include some exemplary discussion of most research frontiers. Topics include objective Bayesian inference, shrinkage estimation and other decision based estimation, model selection and testing, nonparametric Bayes, the interface of Bayesian and frequentist inference, data mining and machine learning, methods for categorical and spatio-temporal data analysis and posterior simulation methods. Several major application areas are covered: computer models, Bayesian clinical trial design, epidemiology, phylogenetics, bioinformatics, climate modeling and applications in political science, finance and marketing. As a review of current research in Bayesian analysis the book presents a balance between theory and applications. The lack of a clear demarcation between theoretical and applied research is a reflection of the highly interdisciplinary and often applied nature of research in Bayesian statistics. The book is intended as an update for researchers in Bayesian statistics, including non-statisticians who make use of Bayesian inference to address substantive research questions in other fields. It would also be useful for graduate students and research scholars in statistics or biostatistics who wish to acquaint themselves with current research frontiers.
