Application Of Omics Ai And Blockchain In Bioinformatics Research
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| Author | : Jeffrey J P Tsai |
| Publisher | : World Scientific |
| Total Pages | : 207 |
| Release | : 2019-10-14 |
| Genre | : Science |
| ISBN | : 9811203598 |
With the increasing availability of omics data and mounting evidence of the usefulness of computational approaches to tackle multi-level data problems in bioinformatics and biomedical research in this post-genomics era, computational biology has been playing an increasingly important role in paving the way as basis for patient-centric healthcare.Two such areas are: (i) implementing AI algorithms supported by biomedical data would deliver significant benefits/improvements towards the goals of precision medicine (ii) blockchain technology will enable medical doctors to securely and privately build personal healthcare records, and identify the right therapeutic treatments and predict the progression of the diseases.A follow-up in the publication of our book Computation Methods with Applications in Bioinformatics Analysis (2017), topics in this volume include: clinical bioinformatics, omics-based data analysis, Artificial Intelligence (AI), blockchain, big data analytics, drug discovery, RNA-seq analysis, tensor decomposition and Boolean network.
| Author | : Jeffrey J.-P. Tsai |
| Publisher | : |
| Total Pages | : 208 |
| Release | : 2019 |
| Genre | : Artificial intelligence |
| ISBN | : 9789811203589 |
"With the increasing availability of omics data and mounting evidence of the usefulness of computational approaches to tackle multi-level data problems in bioinformatics and biomedical research in this post-genomics era, computational biology has been playing an increasingly important role in paving the way as basis for patient-centric healthcare. Two such areas are: (I) implementing AI algorithms supported by biomedical data would deliver significant benefits/improvements towards the goals of precision medicine (II) blockchain technology will enable medical doctors to securely and privately build personal healthcare records, and identify the right therapeutic treatments and predict the progression of the diseases. A follow-up in the publication of our book Computation Methods with Applications in Bioinformatics Analysis (2017), topics in this volume include: clinical bioinformatics, Omics-based data analysis, Artificial Intelligence (AI), blockchain, big data analytics, drug discovery, RNA-seq analysis, tensor decomposition and Boolean network"--
| Author | : Rajiv Pandey |
| Publisher | : Elsevier |
| Total Pages | : 478 |
| Release | : 2023-04-08 |
| Genre | : Science |
| ISBN | : 0323961479 |
Distributed Computing to Blockchain: Architecture, Technology, and Applications provides researchers, computer scientists, and data scientists with a comprehensive and applied reference covering the evolution of distributed systems computing into blockchain and associated systems. Divided into three major sections, the book explores the basic topics in the blockchain space extending from distributed systems architecture, distributed ledger, decentralized web to introductory aspects of cryptoeconomics (cryptography and economics) of decentralized applications. The book further explores advanced concepts such as smart contracts; distributed token mining, initial coin offerings; proof of work; public, private, and other blockchains; cryptography; security; and blockchains. The book goes on to review byzantine fault tolerance, distributed ledgers versus blockchains, and blockchain protocols. The final section covers multiple use cases and applications of distributed computing and the future directions for blockchains. - Presented as a focused reference handbook describing the evolution of distributed systems, blockchain, and consensus algorithms emphasizing the architectural and functional aspects - Integrates the various concepts of cryptography in blockchain and further extends to blockchain forensics - Provides insight and detailed Interpretation of algorithms for consensus in blockchains
| Author | : Russ B Altman |
| Publisher | : World Scientific |
| Total Pages | : 380 |
| Release | : 2020-11-24 |
| Genre | : Computers |
| ISBN | : 9811232717 |
The Pacific Symposium on Biocomputing (PSB) 2021 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2021 will be held on a virtual platform at psb.stanford.edu/ on January 5-7, 2021. Tutorials and workshops will be offered prior to the start of the conference.PSB 2021 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's 'hot topics.' In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field.
| Author | : Saini, Hemraj |
| Publisher | : IGI Global |
| Total Pages | : 285 |
| Release | : 2020-08-14 |
| Genre | : Computers |
| ISBN | : 1799834468 |
Data has cemented itself as a building block of daily life. However, surrounding oneself with great quantities of information heightens risks to one’s personal privacy. Additionally, the presence of massive amounts of information prompts researchers into how best to handle and disseminate it. Research is necessary to understand how to cope with the current technological requirements. Large-Scale Data Streaming, Processing, and Blockchain Security is a collection of innovative research that explores the latest methodologies, modeling, and simulations for coping with the generation and management of large-scale data in both scientific and individual applications. Featuring coverage on a wide range of topics including security models, internet of things, and collaborative filtering, this book is ideally designed for entrepreneurs, security analysts, IT consultants, security professionals, programmers, computer technicians, data scientists, technology developers, engineers, researchers, academicians, and students.
| Author | : Y-h. Taguchi |
| Publisher | : Springer Nature |
| Total Pages | : 329 |
| Release | : 2019-08-23 |
| Genre | : Technology & Engineering |
| ISBN | : 3030224562 |
This book proposes applications of tensor decomposition to unsupervised feature extraction and feature selection. The author posits that although supervised methods including deep learning have become popular, unsupervised methods have their own advantages. He argues that this is the case because unsupervised methods are easy to learn since tensor decomposition is a conventional linear methodology. This book starts from very basic linear algebra and reaches the cutting edge methodologies applied to difficult situations when there are many features (variables) while only small number of samples are available. The author includes advanced descriptions about tensor decomposition including Tucker decomposition using high order singular value decomposition as well as higher order orthogonal iteration, and train tenor decomposition. The author concludes by showing unsupervised methods and their application to a wide range of topics. Allows readers to analyze data sets with small samples and many features; Provides a fast algorithm, based upon linear algebra, to analyze big data; Includes several applications to multi-view data analyses, with a focus on bioinformatics.
| Author | : Masakazu Sengoku |
| Publisher | : World Scientific |
| Total Pages | : 409 |
| Release | : 2023-01-30 |
| Genre | : Technology & Engineering |
| ISBN | : 9811255318 |
This comprehensive compendium discusses the basics of graph theory to its application, focusing on the application of graph theory to mobile communications.A mobile communication connects a mobile terminal and a base station wirelessly, and the base station enables communications all over the world via a wired and satellite communication system. This means that the mobile communication system includes wire and wireless technologies, and also hardware such as analog electric circuits, digital circuits and a software part such as computer algorithms.This useful reference text deeply studies how the network structure influences the performance of the corresponding system.
| Author | : Zoran Stamenkovic |
| Publisher | : World Scientific |
| Total Pages | : 430 |
| Release | : 2020-11-27 |
| Genre | : Computers |
| ISBN | : 981121073X |
Today's integrated silicon circuits and systems for wireless communications are of a huge complexity.This unique compendium covers all the steps (from the system-level to the transistor-level) necessary to design, model, verify, implement, and test a silicon system. It bridges the gap between the system-world and the transistor-world (between communication, system, circuit, device, and test engineers).It is extremely important nowadays (and will be more important in the future) for communication, system, and circuit engineers to understand the physical implications of system and circuit solutions based on hardware/software co-design as well as for device and test engineers to cope with the system and circuit requirements in terms of power, speed, and data throughput.Related Link(s)
| Author | : Sujata Dash |
| Publisher | : John Wiley & Sons |
| Total Pages | : 450 |
| Release | : 2021-08-24 |
| Genre | : Computers |
| ISBN | : 111971124X |
BIOMEDICAL DATA MINING FOR INFORMATION RETRIEVAL This book not only emphasizes traditional computational techniques, but discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. Biomedical Data Mining for Information Retrieval comprehensively covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally. These images are mainly in the form of computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients’ biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions relating to healthcare. Image mining in medicine can help to uncover new relationships between data and reveal new useful information that can be helpful for doctors in treating their patients. Audience Researchers in various fields including computer science, medical informatics, healthcare IOT, artificial intelligence, machine learning, image processing, clinical big data analytics.
| Author | : Jeffrey J P Tsai |
| Publisher | : World Scientific |
| Total Pages | : 233 |
| Release | : 2017-06-09 |
| Genre | : Science |
| ISBN | : 981320799X |
This compendium contains 10 chapters written by world renowned researchers with expertise in semantic computing, genome sequence analysis, biomolecular interaction, time-series microarray analysis, and machine learning algorithms.The salient feature of this book is that it highlights eight types of computational techniques to tackle different biomedical applications. These techniques include unsupervised learning algorithms, principal component analysis, fuzzy integral, graph-based ensemble clustering method, semantic analysis, interolog approach, molecular simulations and enzyme kinetics.The unique volume will be a useful reference material and an inspirational read for advanced undergraduate and graduate students, computer scientists, computational biologists, bioinformatics and biomedical professionals.
