Автор: Wong Ka-Chun Название: Big Data Analytics in Genomics ISBN: 3319823124 ISBN-13(EAN): 9783319823126 Издательство: Springer Рейтинг: Цена: 158380.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This contributed volume explores the emerging intersection between big data analytics and genomics. Recent sequencing technologies have enabled high-throughput sequencing data generation for genomics resulting in several international projects which have led to massive genomic data accumulation at an unprecedented pace. To reveal novel genomic insights from this data within a reasonable time frame, traditional data analysis methods may not be sufficient or scalable, forcing the need for big data analytics to be developed for genomics. The computational methods addressed in the book are intended to tackle crucial biological questions using big data, and are appropriate for either newcomers or veterans in the field. This volume offers thirteen peer-reviewed contributions, written by international leading experts from different regions, representing Argentina, Brazil, China, France, Germany, Hong Kong, India, Japan, Spain, and the USA. In particular, the book surveys three main areas: statistical analytics, computational analytics, and cancer genome analytics. Sample topics covered include: statistical methods for integrative analysis of genomic data, computation methods for protein function prediction, and perspectives on machine learning techniques in big data mining of cancer. Self-contained and suitable for graduate students, this book is also designed for bioinformaticians, computational biologists, and researchers in communities ranging from genomics, big data, molecular genetics, data mining, biostatistics, biomedical science, cancer research, medical research, and biology to machine learning and computer science. Readers will find this volume to be an essential read for appreciating the role of big data in genomics, making this an invaluable resource for stimulating further research on the topic.
Автор: Matter, Ulrich Название: Big Data Analytics ISBN: 1032457554 ISBN-13(EAN): 9781032457550 Издательство: Taylor&Francis Рейтинг: Цена: 137810.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Holdaway Keith Название: Harness Oil and Gas Big Data with Analytics ISBN: 1118779312 ISBN-13(EAN): 9781118779316 Издательство: Wiley Рейтинг: Цена: 60720.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Use big data analytics to efficiently drive oil and gas exploration and production Harness Oil and Gas Big Data with Analytics provides a complete view of big data and analytics techniques as they are applied to the oil and gas industry.
Автор: Wolfgang Karl H?rdle; Henry Horng-Shing Lu; Xiaoto Название: Handbook of Big Data Analytics ISBN: 3319182838 ISBN-13(EAN): 9783319182834 Издательство: Springer Рейтинг: Цена: 260870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discoveries from big data. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have a solid background in statistics and computer science.
Автор: Wrembel Название: Big Data Analytics and Knowledge Discovery ISBN: 3031126696 ISBN-13(EAN): 9783031126697 Издательство: Springer Рейтинг: Цена: 65210.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume LNCS 13428 constitutes the papers of the 24 th International Conference on Big Data Analytics and Knowledge Discovery, held in August 2022 in Vienna, Austria. The 12 full papers presented together with 12 short papers in this volume were carefully reviewed and selected from a total of 57 submissions. The papers reflect a wide range of topics in the field of data integration, data warehousing, data analytics, and recently big data analytics, in a broad sense. The main objectives of this event are to explore, disseminate, and exchange knowledge in these fields.
Автор: Taniguchi, Eiichi Название: Urban Freight Analytics ISBN: 1032199369 ISBN-13(EAN): 9781032199368 Издательство: Taylor&Francis Рейтинг: Цена: 94930.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Название: Big data analytics ISBN: 8132238710 ISBN-13(EAN): 9788132238713 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today.
Автор: Atiquzzaman Название: 2021 International Conference on Big Data Analytics for Cyber-Physical System in Smart City ISBN: 9811674655 ISBN-13(EAN): 9789811674655 Издательство: Springer Рейтинг: Цена: 214280.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book gathers a selection of peer-reviewed papers presented at the third Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2021) conference, held in Shanghai, China, on Nov. 27, 2021.
Автор: Wong Название: Big Data Analytics in Genomics ISBN: 3319412787 ISBN-13(EAN): 9783319412788 Издательство: Springer Рейтинг: Цена: 158380.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
This contributed volume explores the emerging intersection between big data analytics and genomics. Recent sequencing technologies have enabled high-throughput sequencing data generation for genomics resulting in several international projects which have led to massive genomic data accumulation at an unprecedented pace. To reveal novel genomic insights from this data within a reasonable time frame, traditional data analysis methods may not be sufficient or scalable, forcing the need for big data analytics to be developed for genomics. The computational methods addressed in the book are intended to tackle crucial biological questions using big data, and are appropriate for either newcomers or veterans in the field.
This volume offers thirteen peer-reviewed contributions, written by international leading experts from different regions, representing Argentina, Brazil, China, France, Germany, Hong Kong, India, Japan, Spain, and the USA. In particular, the book surveys three main areas: statistical analytics, computational analytics, and cancer genome analytics. Sample topics covered include: statistical methods for integrative analysis of genomic data, computation methods for protein function prediction, and perspectives on machine learning techniques in big data mining of cancer. Self-contained and suitable for graduate students, this book is also designed for bioinformaticians, computational biologists, and researchers in communities ranging from genomics, big data, molecular genetics, data mining, biostatistics, biomedical science, cancer research, medical research, and biology to machine learning and computer science. Readers will find this volume to be an essential read for appreciating the role of big data in genomics, making this an invaluable resource for stimulating further research on the topic.
Автор: Kumar R. Lakshmana, Indrakumari R., Balamurugan B. Название: Exploratory Data Analytics for Healthcare ISBN: 0367506912 ISBN-13(EAN): 9780367506919 Издательство: Taylor&Francis Рейтинг: Цена: 148010.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Exploratory data analysis helps to recognize natural patterns hidden in the data. This book describes the tools for hypothesis generation by visualizing data through graphical representation and provides insight into advanced analytics concepts in an easy way.
Название: 2021 International Conference on Big Data Analytics for Cyber-Physical System in ISBN: 981167468X ISBN-13(EAN): 9789811674686 Издательство: Springer Рейтинг: Цена: 214280.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book gathers a selection of peer-reviewed papers presented at the third Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2021) conference, held in Shanghai, China, on Nov. 27, 2021. The contributions, prepared by an international team of scientists and engineers, cover the latest advances made in the field of machine learning, and big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.
Автор: Qu Название: Personalized Privacy Protection in Big Data ISBN: 9811637520 ISBN-13(EAN): 9789811637520 Издательство: Springer Рейтинг: Цена: 60550.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents the data privacy protection which has been extensively applied in our current era of big data. However, research into big data privacy is still in its infancy. Given the fact that existing protection methods can result in low data utility and unbalanced trade-offs, personalized privacy protection has become a rapidly expanding research topic. In this book, the authors explore emerging threats and existing privacy protection methods, and discuss in detail both the advantages and disadvantages of personalized privacy protection. Traditional methods, such as differential privacy and cryptography, are discussed using a comparative and intersectional approach, and are contrasted with emerging methods like federated learning and generative adversarial nets. The advances discussed cover various applications, e.g. cyber-physical systems, social networks, and location-based services. Given its scope, the book is of interest to scientists, policy-makers, researchers, and postgraduates alike.
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