Scalable Big Data Analytics For Protein Bioinformatics


Scalable Big Data Analytics For Protein Bioinformatics
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Scalable Big Data Analytics For Protein Bioinformatics


Scalable Big Data Analytics For Protein Bioinformatics
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Author : Dariusz Mrozek
language : en
Publisher: Springer
Release Date : 2018-09-25

Scalable Big Data Analytics For Protein Bioinformatics written by Dariusz Mrozek and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-25 with Computers categories.


This book presents a focus on proteins and their structures. The text describes various scalable solutions for protein structure similarity searching, carried out at main representation levels and for prediction of 3D structures of proteins. Emphasis is placed on techniques that can be used to accelerate similarity searches and protein structure modeling processes. The content of the book is divided into four parts. The first part provides background information on proteins and their representation levels, including a formal model of a 3D protein structure used in computational processes, and a brief overview of the technologies used in the solutions presented in the book. The second part of the book discusses Cloud services that are utilized in the development of scalable and reliable cloud applications for 3D protein structure similarity searching and protein structure prediction. The third part of the book shows the utilization of scalable Big Data computational frameworks, like Hadoop and Spark, in massive 3D protein structure alignments and identification of intrinsically disordered regions in protein structures. The fourth part of the book focuses on finding 3D protein structure similarities, accelerated with the use of GPUs and the use of multithreading and relational databases for efficient approximate searching on protein secondary structures. The book introduces advanced techniques and computational architectures that benefit from recent achievements in the field of computing and parallelism. Recent developments in computer science have allowed algorithms previously considered too time-consuming to now be efficiently used for applications in bioinformatics and the life sciences. Given its depth of coverage, the book will be of interest to researchers and software developers working in the fields of structural bioinformatics and biomedical databases.



Machine Learning Techniques On Gene Function Prediction Volume Ii


Machine Learning Techniques On Gene Function Prediction Volume Ii
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Author : Quan Zou
language : en
Publisher: Frontiers Media SA
Release Date : 2023-04-11

Machine Learning Techniques On Gene Function Prediction Volume Ii written by Quan Zou and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-11 with Science categories.




Big Data Analytics In Genomics


Big Data Analytics In Genomics
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Author : Ka-Chun Wong
language : en
Publisher: Springer
Release Date : 2016-10-24

Big Data Analytics In Genomics written by Ka-Chun Wong and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-24 with Computers categories.


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.



Big Data Analytics In Bioinformatics And Healthcare


Big Data Analytics In Bioinformatics And Healthcare
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Author : Wang, Baoying
language : en
Publisher: IGI Global
Release Date : 2014-10-31

Big Data Analytics In Bioinformatics And Healthcare written by Wang, Baoying and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-31 with Computers categories.


As technology evolves and electronic data becomes more complex, digital medical record management and analysis becomes a challenge. In order to discover patterns and make relevant predictions based on large data sets, researchers and medical professionals must find new methods to analyze and extract relevant health information. Big Data Analytics in Bioinformatics and Healthcare merges the fields of biology, technology, and medicine in order to present a comprehensive study on the emerging information processing applications necessary in the field of electronic medical record management. Complete with interdisciplinary research resources, this publication is an essential reference source for researchers, practitioners, and students interested in the fields of biological computation, database management, and health information technology, with a special focus on the methodologies and tools to manage massive and complex electronic information.



Beyond Databases Architectures And Structures Paving The Road To Smart Data Processing And Analysis


Beyond Databases Architectures And Structures Paving The Road To Smart Data Processing And Analysis
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Author : Stanisław Kozielski
language : en
Publisher: Springer
Release Date : 2019-05-07

Beyond Databases Architectures And Structures Paving The Road To Smart Data Processing And Analysis written by Stanisław Kozielski and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-07 with Computers categories.


This book constitutes the refereed proceedings of the 15th International Conference entitled Beyond Databases, Architectures and Structures, BDAS 2019, held in Ustroń, Poland, in May 2019. It consists of 26 carefully reviewed papers selected from 69 submissions. The papers are organized in topical sections, namely big data and cloud computing; architectures, structures and algorithms for efficient data processing and analysis; artificial intelligence, data mining and knowledge discovery; image analysis and multimedia mining; bioinformatics and biomedical data analysis; industrial applications; networks and security.



Machine Learning Techniques On Gene Function Prediction


Machine Learning Techniques On Gene Function Prediction
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Author : Quan Zou
language : en
Publisher: Frontiers Media SA
Release Date : 2019-12-04

Machine Learning Techniques On Gene Function Prediction written by Quan Zou and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-04 with categories.




Computational Science Iccs 2020


Computational Science Iccs 2020
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Author : Valeria V. Krzhizhanovskaya
language : en
Publisher: Springer Nature
Release Date : 2020-06-18

Computational Science Iccs 2020 written by Valeria V. Krzhizhanovskaya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-18 with Computers categories.


The seven-volume set LNCS 12137, 12138, 12139, 12140, 12141, 12142, and 12143 constitutes the proceedings of the 20th International Conference on Computational Science, ICCS 2020, held in Amsterdam, The Netherlands, in June 2020.* The total of 101 papers and 248 workshop papers presented in this book set were carefully reviewed and selected from 719 submissions (230 submissions to the main track and 489 submissions to the workshops). The papers were organized in topical sections named: Part I: ICCS Main Track Part II: ICCS Main Track Part III: Track of Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Track of Agent-Based Simulations, Adaptive Algorithms and Solvers; Track of Applications of Computational Methods in Artificial Intelligence and Machine Learning; Track of Biomedical and Bioinformatics Challenges for Computer Science Part IV: Track of Classifier Learning from Difficult Data; Track of Complex Social Systems through the Lens of Computational Science; Track of Computational Health; Track of Computational Methods for Emerging Problems in (Dis-)Information Analysis Part V: Track of Computational Optimization, Modelling and Simulation; Track of Computational Science in IoT and Smart Systems; Track of Computer Graphics, Image Processing and Artificial Intelligence Part VI: Track of Data Driven Computational Sciences; Track of Machine Learning and Data Assimilation for Dynamical Systems; Track of Meshfree Methods in Computational Sciences; Track of Multiscale Modelling and Simulation; Track of Quantum Computing Workshop Part VII: Track of Simulations of Flow and Transport: Modeling, Algorithms and Computation; Track of Smart Systems: Bringing Together Computer Vision, Sensor Networks and Machine Learning; Track of Software Engineering for Computational Science; Track of Solving Problems with Uncertainties; Track of Teaching Computational Science; Track of UNcErtainty QUantIficatiOn for ComputationAl modeLs *The conference was canceled due to the COVID-19 pandemic.



Cooperative Design Visualization And Engineering


Cooperative Design Visualization And Engineering
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Author : Yuhua Luo
language : en
Publisher: Springer Nature
Release Date : 2021-09-30

Cooperative Design Visualization And Engineering written by Yuhua Luo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-30 with Computers categories.


This book constitutes the proceedings of the 18th International Conference on Cooperative Design, Visualization, and Engineering, CDVE 2021, held in October 2021. Due to COVId-19 pandemic the conference was held virtually. The 25 full papers and 9 short papers presented were carefully reviewed and selected from 69 submissions. The achievement, progress and future challenges are reported in areas such as health care, industrial design, banking IT systems, cultural activities support, operational maritime cybersecurity assurance, emotion communication, and social network data analytics.



Big Data


Big Data
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Author : Nathan Marz
language : en
Publisher: Manning Publications Company
Release Date : 2015

Big Data written by Nathan Marz and has been published by Manning Publications Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Computers categories.


Summary Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book Web-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive. Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases. This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful. What's Inside Introduction to big data systems Real-time processing of web-scale data Tools like Hadoop, Cassandra, and Storm Extensions to traditional database skills About the Authors Nathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing. Table of Contents A new paradigm for Big Data PART 1 BATCH LAYER Data model for Big Data Data model for Big Data: Illustration Data storage on the batch layer Data storage on the batch layer: Illustration Batch layer Batch layer: Illustration An example batch layer: Architecture and algorithms An example batch layer: Implementation PART 2 SERVING LAYER Serving layer Serving layer: Illustration PART 3 SPEED LAYER Realtime views Realtime views: Illustration Queuing and stream processing Queuing and stream processing: Illustration Micro-batch stream processing Micro-batch stream processing: Illustration Lambda Architecture in depth



Big Data Analytics In Chemoinformatics And Bioinformatics


Big Data Analytics In Chemoinformatics And Bioinformatics
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Author : Subhash C. Basak
language : en
Publisher: Elsevier
Release Date : 2022-12-06

Big Data Analytics In Chemoinformatics And Bioinformatics written by Subhash C. Basak and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-06 with Science categories.


Big Data Analytics in Chemoinformatics and Bioinformatics: With Applications to Computer-Aided Drug Design, Cancer Biology, Emerging Pathogens and Computational Toxicology provides an up-to-date presentation of big data analytics methods and their applications in diverse fields. The proper management of big data for decision-making in scientific and social issues is of paramount importance. This book gives researchers the tools they need to solve big data problems in these fields. It begins with a section on general topics that all readers will find useful and continues with specific sections covering a range of interdisciplinary applications. Here, an international team of leading experts review their respective fields and present their latest research findings, with case studies used throughout to analyze and present key information. Brings together the current knowledge on the most important aspects of big data, including analysis using deep learning and fuzzy logic, transparency and data protection, disparate data analytics, and scalability of the big data domain Covers many applications of big data analysis in diverse fields such as chemistry, chemoinformatics, bioinformatics, computer-assisted drug/vaccine design, characterization of emerging pathogens, and environmental protection Highlights the considerable benefits offered by big data analytics to science, in biomedical fields and in industry