Unsupervised Learning Models for Unlabeled Genomic, Transcriptomic & Proteomic Data PDF Download
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Author: Jianing Xi
Publisher: Frontiers Media SA
ISBN: 2889719677
Category : Science
Languages : en
Pages : 109
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Book Description
Author: Jianing Xi
Publisher: Frontiers Media SA
ISBN: 2889719677
Category : Science
Languages : en
Pages : 109
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Book Description
Author: Seth Kwabena Amponsah
Publisher: Springer Nature
ISBN: 3031640217
Category : Pharmacology
Languages : en
Pages : 480
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Book Description
This book gives an overview of pharmacoproteomics and its clinical applications, as well as the latest information on drug mechanisms at the proteome level, the relationship between proteomics and toxicity or resistance, and how proteomics aid in discovery of new drug targets. The book also highlights recent advances in analytical methods, analysis, and interpretation of pharmacoproteomic data. Pharmacoproteomics: Recent Trends and Applications is an ideal book for those working in pharmaceutical industries, as well as scientists, health care professionals, and researchers who work in the field of genomics, pharmacology, pharmacokinetics, toxicology, and pharmaceutical chemistry.
Author: Brian S. Hilbush
Publisher: John Wiley & Sons
ISBN: 1119745632
Category : Technology & Engineering
Languages : en
Pages : 301
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Book Description
Learn how AI and data science are upending the worlds of biology and medicine In Silico Dreams: How Artificial Intelligence and Biotechnology Will Create the Medicines of the Future delivers an illuminating and fresh perspective on the convergence of two powerful technologies: AI and biotech. Accomplished genomics expert, executive, and author Brian Hilbush offers readers a brilliant exploration of the most current work of pioneering tech giants and biotechnology startups who have already started disrupting healthcare. The book provides an in-depth understanding of the sources of innovation that are driving the shift in the pharmaceutical industry away from serendipitous therapeutic discovery and toward engineered medicines and curative therapies. In this fascinating book, you'll discover: An overview of the rise of data science methods and the paradigm shift in biology that led to the in silico revolution An outline of the fundamental breakthroughs in AI and deep learning and their applications across medicine A compelling argument for the notion that AI and biotechnology tools will rapidly accelerate the development of therapeutics A summary of innovative breakthroughs in biotechnology with a focus on gene editing and cell reprogramming technologies for therapeutic development A guide to the startup landscape in AI in medicine, revealing where investments are poised to shape the innovation base for the pharmaceutical industry Perfect for anyone with an interest in scientific topics and technology, In Silico Dreams also belongs on the bookshelves of decision-makers in a wide range of industries, including healthcare, technology, venture capital, and government.
Author: Pardeep Kumar
Publisher: Academic Press
ISBN: 0128217812
Category : Computers
Languages : en
Pages : 460
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Book Description
Machine Learning, Big Data, and IoT for Medical Informatics focuses on the latest techniques adopted in the field of medical informatics. In medical informatics, machine learning, big data, and IOT-based techniques play a significant role in disease diagnosis and its prediction. In the medical field, the structure of data is equally important for accurate predictive analytics due to heterogeneity of data such as ECG data, X-ray data, and image data. Thus, this book focuses on the usability of machine learning, big data, and IOT-based techniques in handling structured and unstructured data. It also emphasizes on the privacy preservation techniques of medical data. This volume can be used as a reference book for scientists, researchers, practitioners, and academicians working in the field of intelligent medical informatics. In addition, it can also be used as a reference book for both undergraduate and graduate courses such as medical informatics, machine learning, big data, and IoT. - Explains the uses of CNN, Deep Learning and extreme machine learning concepts for the design and development of predictive diagnostic systems. - Includes several privacy preservation techniques for medical data. - Presents the integration of Internet of Things with predictive diagnostic systems for disease diagnosis. - Offers case studies and applications relating to machine learning, big data, and health care analysis.
Author: Sanjeeva Srivastava
Publisher: CRC Press
ISBN: 1000595609
Category : Science
Languages : en
Pages : 237
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Book Description
"COVID-19 and Omics Technologies" is a comprehensive, integrative assessment of recent information and knowledge collected on SARS-CoV-2 and COVID-19 during the pandemic based on omics technologies. It demonstrates how omics technologies could better investigate the infectious disease and propose solutions to the current concerns. The value of multi-omics technologies in understanding disease etiology and host response, discovering infection biomarkers and illness prediction, identifying vaccine candidates, discovering therapeutic targets, and tracing pathogen evolution is discussed in this book. These factors combine to make it a valuable resource to enhance understanding of both "Omics technology" and "COVID-19" as a disease. The book covers the most recent understanding of COVID-19 and the applications of cutting-edge studies, making it accessible to a large multidisciplinary readership. The book explains how high-throughput technologies and systems biology might assist to solve the pandemic’s challenges and deconstruct and appreciate the substantial contributions that omics technologies have made in predicting the path of this unforeseeable pandemic. Features: In-depth summary of clinical presentation, epidemiological impact, and long-term sequelae of COVID-19 pandemic. A systematic overview of omics-based approaches to the study of COVID-19 biology. Recent research results and some pointers to future advancements in methodologies used. Detailed examples from recent studies on COVID-19 encompassing different omics methodologies. A detailed description of methodologies and notes on the applications of state-of-the-art technologies. This book is intended for scientists who need to understand the biology of COVID-19 from the perspective of omics investigations, as well as researchers who want to employ omics-based technologies in disease biology.
Author: Israel Tojal Da Silva
Publisher: Frontiers Media SA
ISBN: 283250020X
Category : Science
Languages : en
Pages : 149
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Book Description
Author: George Bebis
Publisher: Frontiers Media SA
ISBN: 2832536646
Category : Medical
Languages : en
Pages : 374
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Book Description
Author: Harry Yang
Publisher: CRC Press
ISBN: 100065267X
Category : Business & Economics
Languages : en
Pages : 335
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Book Description
The confluence of big data, artificial intelligence (AI), and machine learning (ML) has led to a paradigm shift in how innovative medicines are developed and healthcare delivered. To fully capitalize on these technological advances, it is essential to systematically harness data from diverse sources and leverage digital technologies and advanced analytics to enable data-driven decisions. Data science stands at a unique moment of opportunity to lead such a transformative change. Intended to be a single source of information, Data Science, AI, and Machine Learning in Drug Research and Development covers a wide range of topics on the changing landscape of drug R & D, emerging applications of big data, AI and ML in drug development, and the build of robust data science organizations to drive biopharmaceutical digital transformations. Features Provides a comprehensive review of challenges and opportunities as related to the applications of big data, AI, and ML in the entire spectrum of drug R & D Discusses regulatory developments in leveraging big data and advanced analytics in drug review and approval Offers a balanced approach to data science organization build Presents real-world examples of AI-powered solutions to a host of issues in the lifecycle of drug development Affords sufficient context for each problem and provides a detailed description of solutions suitable for practitioners with limited data science expertise
Author: Tiratha Raj Singh
Publisher: CRC Press
ISBN: 1003813208
Category : Computers
Languages : en
Pages : 376
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Book Description
Bioinformatics and Computational Biology: Technological Advancements, Applications and Opportunities is an invaluable resource for general and applied researchers who analyze biological data that is generated, at an unprecedented rate, at the global level. After careful evaluation of the requirements for current trends in bioinformatics and computational biology, it is anticipated that the book will provide an insightful resource to the academic and scientific community. Through a myriad of computational resources, algorithms, and methods, it equips readers with the confidence to both analyze biological data and estimate predictions. The book offers comprehensive coverage of the most essential and emerging topics: Cloud-based monitoring of bioinformatics multivariate data with cloud platforms Machine learning and deep learning in bioinformatics Quantum machine learning for biological applications Integrating machine learning strategies with multiomics to augment prognosis in chronic diseases Biomedical engineering Next generation sequencing techniques and applications Computational systems biology and molecular evolution While other books may touch on some of the same issues and nuances of biological data analysis, they neglect to feature bioinformatics and computational biology exclusively, and as exhaustively. This book's abundance of several subtopics related to almost all of the regulatory activities of biomolecules from where real data is being generated brings an added dimension.
Author: Anais Rameau
Publisher: Elsevier Health Sciences
ISBN: 0443313539
Category : Medical
Languages : en
Pages : 249
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Book Description
In this issue of Otolaryngologic Clinics, guest editors Drs. Anais Rameau and Matthew G. Crowson bring their considerable expertise to the topic of Artificial Intelligence in Otolaryngology. Top experts in the field cover timely topics in the areas of Best Practices, AI Modalities, Implementation and Governance, and Subspecialty AI. - Contains 17 relevant, practice-oriented topics including clinical data/machine learning; generative AI and otolaryngology-head and neck surgery; ethics; AI in otology and neurotology; AI in facial plastic and reconstructive surgery; AI in pediatric otolaryngology; and more. - Provides in-depth clinical reviews on artificial intelligence in otolaryngology, offering actionable insights for clinical practice. - Presents the latest information on this timely, focused topic under the leadership of experienced editors in the field. Authors synthesize and distill the latest research and practice guidelines to create clinically significant, topic-based reviews.
