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Author:
Publisher: Elsevier
ISBN: 0128114320
Category : Medical
Languages : en
Pages : 3421
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Book Description
Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics, Three Volume Set combines elements of computer science, information technology, mathematics, statistics and biotechnology, providing the methodology and in silico solutions to mine biological data and processes. The book covers Theory, Topics and Applications, with a special focus on Integrative –omics and Systems Biology. The theoretical, methodological underpinnings of BCB, including phylogeny are covered, as are more current areas of focus, such as translational bioinformatics, cheminformatics, and environmental informatics. Finally, Applications provide guidance for commonly asked questions. This major reference work spans basic and cutting-edge methodologies authored by leaders in the field, providing an invaluable resource for students, scientists, professionals in research institutes, and a broad swath of researchers in biotechnology and the biomedical and pharmaceutical industries. Brings together information from computer science, information technology, mathematics, statistics and biotechnology Written and reviewed by leading experts in the field, providing a unique and authoritative resource Focuses on the main theoretical and methodological concepts before expanding on specific topics and applications Includes interactive images, multimedia tools and crosslinking to further resources and databases
Author:
Publisher: Elsevier
ISBN: 0128114320
Category : Medical
Languages : en
Pages : 3421
Get Book Here
Book Description
Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics, Three Volume Set combines elements of computer science, information technology, mathematics, statistics and biotechnology, providing the methodology and in silico solutions to mine biological data and processes. The book covers Theory, Topics and Applications, with a special focus on Integrative –omics and Systems Biology. The theoretical, methodological underpinnings of BCB, including phylogeny are covered, as are more current areas of focus, such as translational bioinformatics, cheminformatics, and environmental informatics. Finally, Applications provide guidance for commonly asked questions. This major reference work spans basic and cutting-edge methodologies authored by leaders in the field, providing an invaluable resource for students, scientists, professionals in research institutes, and a broad swath of researchers in biotechnology and the biomedical and pharmaceutical industries. Brings together information from computer science, information technology, mathematics, statistics and biotechnology Written and reviewed by leading experts in the field, providing a unique and authoritative resource Focuses on the main theoretical and methodological concepts before expanding on specific topics and applications Includes interactive images, multimedia tools and crosslinking to further resources and databases
Author: David Camacho
Publisher: Springer Nature
ISBN: 3030966275
Category : Technology & Engineering
Languages : en
Pages : 464
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Book Description
This book collects 43 regular papers received from 18 countries that present innovative advances in intelligent and distributed computing, encompassing both architectural and algorithmic results related to these fields. Significant attention is given to new models, techniques, and applications for distributed intelligent architectures and high-performance architectures, machine learning techniques, Internet of Things, blockchain, intelligent transport systems, data analytics, trust and reputation systems, and many others. The book includes the peer-reviewed proceedings of the 14th International Symposium on Intelligent Distributed Computing (IDC 2021), which was held in online mode due to the COVSARS2 pandemic situation, during September 16–18, 2021. The IDC 2021 event included sessions on Internet of Things, data analytics, machine learning, multi-agent systems, algorithms, future intelligent transport solutions, blockchain, intelligent distributed computing for cyber-physical security, and security and trust and reputation in intelligent environments.
Author: Felix Kallenborn
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
With the technological advances in the field of genomics and sequencing, the processing of vast amounts of generated data becomes more and more challenging. Nowadays, software for processing large-scale datasets of sequencing reads may take hours to days to complete, even on high-end workstations. This explains the need for new approaches to achieve faster, high-performance applications. In contrast to traditional CPU-based software, algorithms utilizing the massively-parallel many-core architecture and fast memory of GPUs are potentially able to deliver the desired performance in many fields. In this thesis, we introduce two novel GPU-accelerated applications, CARE and CAREx, for common steps in sequence processing pipelines, error correction and read extension of Next Generation Sequencing (NGS) Illumina data, to improve the results of down-stream data analysis. To the best of our knowledge, CARE and CAREx are the first modern GPU-accelerated solutions for the respective problems. A key component of our algorithm is the identification of similar DNA sequences within a dataset. For this purpose, we developed a minhashing-based index data structure for large-scale read datasets. In conjunction with our fast bit-parallel shifted hamming distance computations, this allows for the efficient identification of similar reads. The resulting set of similar sequences is subsequently arranged into a gap-free multiple-sequence alignment to solve the problem at hand. Sequencing machines introduce both systematic errors and random errors. CARE, Context-Aware Read Error corrector, accurately removes errors introduced by NGS sequencing machines during the initial sequencing of a biological sample. With the help of a pre-trained Random Forest, CARE generates two orders-of-magnitude fewer false positives than its competitors. At the same time, it shows similar numbers of true positives. Read extension describes the process of elongating DNA sequences. The presence of longer sequences improves the resolution of more, larger structures within a genome. CAREx, Context-Aware Read Extender, produces longer sequences, so called pseudo-long reads, by connecting the two reads of read pairs which were sequenced in close proximity. Evaluation shows that CAREx produces significantly more highly accurate pseudo-long reads than the state-of-the-art. With algorithms tailored towards high-performance GPU computations, both CARE and CAREx run significantly faster than the CPU-based competitors, while, at the same time, produce more accurate results. The processing of a large Human dataset with 30x coverage with CARE requires less than 30 minutes using a single A100 GPU. This time can be further reduced down to 10 minutes on multi-GPU systems. In contrast, CPU-based tools like Musket or BFC take 3 hours and 1.5 hours, respectively. Read extension of a Human dataset with CAREx takes 3.3 hours to complete on a single GPU, whereas Konnector2 requires over a day to complete. This shows that large-scale sequence processing can greatly benefit from the usage of GPUs, and that multiple-sequence alignment-based algorithms should be considered despite their increased complexity because they provide great accuracy. While our general building blocks have been tailored towards our needs for error correction and read extension, they could also prove useful in other GPU-accelerated applications that process sequence data.
Author: Chao Wang
Publisher: CRC Press
ISBN: 1040031986
Category : Computers
Languages : en
Pages : 417
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Book Description
With the end of Moore’s Law, domain-specific architecture (DSA) has become a crucial mode of implementing future computing architectures. This book discusses the system-level design methodology of DSAs and their applications, providing a unified design process that guarantees functionality, performance, energy efficiency, and real-time responsiveness for the target application. DSAs often start from domain-specific algorithms or applications, analyzing the characteristics of algorithmic applications, such as computation, memory access, and communication, and proposing the heterogeneous accelerator architecture suitable for that particular application. This book places particular focus on accelerator hardware platforms and distributed systems for various novel applications, such as machine learning, data mining, neural networks, and graph algorithms, and also covers RISC-V open-source instruction sets. It briefly describes the system design methodology based on DSAs and presents the latest research results in academia around domain-specific acceleration architectures. Providing cutting-edge discussion of big data and artificial intelligence scenarios in contemporary industry and typical DSA applications, this book appeals to industry professionals as well as academicians researching the future of computing in these areas.
Author: Mourad Elloumi
Publisher: John Wiley & Sons
ISBN: 1118101987
Category : Science
Languages : en
Pages : 1027
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Book Description
This book represents the most comprehensive and up-to-date collection of information on the topic of computational molecular biology. Bringing the most recent research into the forefront of discussion, Algorithms in Computational Molecular Biology studies the most important and useful algorithms currently being used in the field, and provides related problems. It also succeeds where other titles have failed, in offering a wide range of information from the introductory fundamentals right up to the latest, most advanced levels of study.
Author: Efthyvoulos Kyriacou
Publisher: Springer
ISBN: 3319327038
Category : Technology & Engineering
Languages : en
Pages : 1384
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Book Description
This volume presents the proceedings of Medicon 2016, held in Paphos, Cyprus. Medicon 2016 is the XIV in the series of regional meetings of the International Federation of Medical and Biological Engineering (IFMBE) in the Mediterranean. The goal of Medicon 2016 is to provide updated information on the state of the art on Medical and Biological Engineering and Computing under the main theme “Systems Medicine for the Delivery of Better Healthcare Services”. Medical and Biological Engineering and Computing cover complementary disciplines that hold great promise for the advancement of research and development in complex medical and biological systems. Research and development in these areas are impacting the science and technology by advancing fundamental concepts in translational medicine, by helping us understand human physiology and function at multiple levels, by improving tools and techniques for the detection, prevention and treatment of disease. Medicon 2016 provides a common platform for the cross fertilization of ideas, and to help shape knowledge and scientific achievements by bridging complementary disciplines into an interactive and attractive forum under the special theme of the conference that is Systems Medicine for the Delivery of Better Healthcare Services. The programme consists of some 290 invited and submitted papers on new developments around the Conference theme, presented in 3 plenary sessions, 29 parallel scientific sessions and 12 special sessions.
Author: Arun Kumar Sangaiah
Publisher: Academic Press
ISBN: 0128172932
Category : Technology & Engineering
Languages : en
Pages : 282
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Book Description
Deep Learning and Parallel Computing Environment for Bioengineering Systems delivers a significant forum for the technical advancement of deep learning in parallel computing environment across bio-engineering diversified domains and its applications. Pursuing an interdisciplinary approach, it focuses on methods used to identify and acquire valid, potentially useful knowledge sources. Managing the gathered knowledge and applying it to multiple domains including health care, social networks, mining, recommendation systems, image processing, pattern recognition and predictions using deep learning paradigms is the major strength of this book. This book integrates the core ideas of deep learning and its applications in bio engineering application domains, to be accessible to all scholars and academicians. The proposed techniques and concepts in this book can be extended in future to accommodate changing business organizations' needs as well as practitioners' innovative ideas. - Presents novel, in-depth research contributions from a methodological/application perspective in understanding the fusion of deep machine learning paradigms and their capabilities in solving a diverse range of problems - Illustrates the state-of-the-art and recent developments in the new theories and applications of deep learning approaches applied to parallel computing environment in bioengineering systems - Provides concepts and technologies that are successfully used in the implementation of today's intelligent data-centric critical systems and multi-media Cloud-Big data
Author: Eric Cheng-yu Lee
Publisher: World Scientific
ISBN: 9813230533
Category : Science
Languages : en
Pages : 277
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Book Description
Biologists find computing bewildering; yet they are expected to be able to process the voluminous data available from the machines they buy and the datasets that has accumulated in genomic databanks worldwide. It is now increasingly difficult for them to avoid dealing with large volumes of data, that goes beyond just doing manual programming.Most books in this realm are full of equations and complex code but this book gives a much gentler entry point particularly for biologists, with code snippets users can use to cut and paste, and run on their Linux or MacOSX operating system or cloud instance. It also provides a step by step installation instructions which they can easily follow. Those who are in the field of genome sequencing and already familiar with the procedures of analysis, may also find this book useful in closing some knowledge gaps.High throughput sequencing requires high throughput and high performance computing. This book provides a gentle entry to high throughput sequencing by dealing with simple skills which the average biologist is increasingly required to master. You will find this book a breeze to read, and some suggestions in this book maybe new to you, something you might want to try out.
Author: Pavan Balaji
Publisher: MIT Press
ISBN: 0262528819
Category : Computers
Languages : en
Pages : 488
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Book Description
An overview of the most prominent contemporary parallel processing programming models, written in a unique tutorial style. With the coming of the parallel computing era, computer scientists have turned their attention to designing programming models that are suited for high-performance parallel computing and supercomputing systems. Programming parallel systems is complicated by the fact that multiple processing units are simultaneously computing and moving data. This book offers an overview of some of the most prominent parallel programming models used in high-performance computing and supercomputing systems today. The chapters describe the programming models in a unique tutorial style rather than using the formal approach taken in the research literature. The aim is to cover a wide range of parallel programming models, enabling the reader to understand what each has to offer. The book begins with a description of the Message Passing Interface (MPI), the most common parallel programming model for distributed memory computing. It goes on to cover one-sided communication models, ranging from low-level runtime libraries (GASNet, OpenSHMEM) to high-level programming models (UPC, GA, Chapel); task-oriented programming models (Charm++, ADLB, Scioto, Swift, CnC) that allow users to describe their computation and data units as tasks so that the runtime system can manage computation and data movement as necessary; and parallel programming models intended for on-node parallelism in the context of multicore architecture or attached accelerators (OpenMP, Cilk Plus, TBB, CUDA, OpenCL). The book will be a valuable resource for graduate students, researchers, and any scientist who works with data sets and large computations. Contributors Timothy Armstrong, Michael G. Burke, Ralph Butler, Bradford L. Chamberlain, Sunita Chandrasekaran, Barbara Chapman, Jeff Daily, James Dinan, Deepak Eachempati, Ian T. Foster, William D. Gropp, Paul Hargrove, Wen-mei Hwu, Nikhil Jain, Laxmikant Kale, David Kirk, Kath Knobe, Ariram Krishnamoorthy, Jeffery A. Kuehn, Alexey Kukanov, Charles E. Leiserson, Jonathan Lifflander, Ewing Lusk, Tim Mattson, Bruce Palmer, Steven C. Pieper, Stephen W. Poole, Arch D. Robison, Frank Schlimbach, Rajeev Thakur, Abhinav Vishnu, Justin M. Wozniak, Michael Wilde, Kathy Yelick, Yili Zheng
Author: Rashid Mehmood
Publisher: Springer
ISBN: 3030137058
Category : Technology & Engineering
Languages : en
Pages : 667
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Book Description
This book provides a multidisciplinary view of smart infrastructure through a range of diverse introductory and advanced topics. The book features an array of subjects that include: smart cities and infrastructure, e-healthcare, emergency and disaster management, Internet of Vehicles, supply chain management, eGovernance, and high performance computing. The book is divided into five parts: Smart Transportation, Smart Healthcare, Miscellaneous Applications, Big Data and High Performance Computing, and Internet of Things (IoT). Contributions are from academics, researchers, and industry professionals around the world. Features a broad mix of topics related to smart infrastructure and smart applications, particularly high performance computing, big data, and artificial intelligence; Includes a strong emphasis on methodological aspects of infrastructure, technology and application development; Presents a substantial overview of research and development on key economic sectors including healthcare and transportation.
