Data Science Ai And Machine Learning In Drug Development

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Data Science, AI, and Machine Learning in Drug Development

Author : Harry Yang
Publisher : CRC Press
ISBN 13 : 100065267X
Total Pages : 335 pages
Book Rating : 4.0/5 (6 download)

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Book Synopsis Data Science, AI, and Machine Learning in Drug Development by : Harry Yang

Download or read book Data Science, AI, and Machine Learning in Drug Development written by Harry Yang and published by CRC Press. This book was released on 2022-10-04 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Data Science, AI, and Machine Learning in Drug Development

Author : Harry Yang
Publisher :
ISBN 13 : 9780367714413
Total Pages : 0 pages
Book Rating : 4.7/5 (144 download)

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Book Synopsis Data Science, AI, and Machine Learning in Drug Development by : Harry Yang

Download or read book Data Science, AI, and Machine Learning in Drug Development written by Harry Yang and published by . This book was released on 2022-10 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The confluence of big data, AI, and machine learning 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 machine learning 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 machine learning 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 detailed description of solutions suitable for practitioners with limited data science expertise

The Era of Artificial Intelligence, Machine Learning, and Data Science in the Pharmaceutical Industry

Author : Stephanie K. Ashenden
Publisher : Academic Press
ISBN 13 : 0128204494
Total Pages : 266 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis The Era of Artificial Intelligence, Machine Learning, and Data Science in the Pharmaceutical Industry by : Stephanie K. Ashenden

Download or read book The Era of Artificial Intelligence, Machine Learning, and Data Science in the Pharmaceutical Industry written by Stephanie K. Ashenden and published by Academic Press. This book was released on 2021-04-23 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Era of Artificial Intelligence, Machine Learning and Data Science in the Pharmaceutical Industry examines the drug discovery process, assessing how new technologies have improved effectiveness. Artificial intelligence and machine learning are considered the future for a wide range of disciplines and industries, including the pharmaceutical industry. In an environment where producing a single approved drug costs millions and takes many years of rigorous testing prior to its approval, reducing costs and time is of high interest. This book follows the journey that a drug company takes when producing a therapeutic, from the very beginning to ultimately benefitting a patient’s life. This comprehensive resource will be useful to those working in the pharmaceutical industry, but will also be of interest to anyone doing research in chemical biology, computational chemistry, medicinal chemistry and bioinformatics. Demonstrates how the prediction of toxic effects is performed, how to reduce costs in testing compounds, and its use in animal research Written by the industrial teams who are conducting the work, showcasing how the technology has improved and where it should be further improved Targets materials for a better understanding of techniques from different disciplines, thus creating a complete guide

Artificial Intelligence in Drug Discovery

Author : Nathan Brown
Publisher : Royal Society of Chemistry
ISBN 13 : 1839160543
Total Pages : 425 pages
Book Rating : 4.8/5 (391 download)

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Book Synopsis Artificial Intelligence in Drug Discovery by : Nathan Brown

Download or read book Artificial Intelligence in Drug Discovery written by Nathan Brown and published by Royal Society of Chemistry. This book was released on 2020-11-04 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Following significant advances in deep learning and related areas interest in artificial intelligence (AI) has rapidly grown. In particular, the application of AI in drug discovery provides an opportunity to tackle challenges that previously have been difficult to solve, such as predicting properties, designing molecules and optimising synthetic routes. Artificial Intelligence in Drug Discovery aims to introduce the reader to AI and machine learning tools and techniques, and to outline specific challenges including designing new molecular structures, synthesis planning and simulation. Providing a wealth of information from leading experts in the field this book is ideal for students, postgraduates and established researchers in both industry and academia.

Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare

Author : Mark Chang
Publisher : CRC Press
ISBN 13 : 1000767302
Total Pages : 235 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare by : Mark Chang

Download or read book Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare written by Mark Chang and published by CRC Press. This book was released on 2020-05-12 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare covers exciting developments at the intersection of computer science and statistics. While much of machine-learning is statistics-based, achievements in deep learning for image and language processing rely on computer science’s use of big data. Aimed at those with a statistical background who want to use their strengths in pursuing AI research, the book: · Covers broad AI topics in drug development, precision medicine, and healthcare. · Elaborates on supervised, unsupervised, reinforcement, and evolutionary learning methods. · Introduces the similarity principle and related AI methods for both big and small data problems. · Offers a balance of statistical and algorithm-based approaches to AI. · Provides examples and real-world applications with hands-on R code. · Suggests the path forward for AI in medicine and artificial general intelligence. As well as covering the history of AI and the innovative ideas, methodologies and software implementation of the field, the book offers a comprehensive review of AI applications in medical sciences. In addition, readers will benefit from hands on exercises, with included R code.

AI to machine learning in Pharmaceuticals

Author : Satyabrata Jena
Publisher : AG PUBLISHING HOUSE (AGPH Books)
ISBN 13 : 9395936754
Total Pages : 224 pages
Book Rating : 4.3/5 (959 download)

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Book Synopsis AI to machine learning in Pharmaceuticals by : Satyabrata Jena

Download or read book AI to machine learning in Pharmaceuticals written by Satyabrata Jena and published by AG PUBLISHING HOUSE (AGPH Books). This book was released on 2022-11-16 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: The convergence of big data, artificial intelligence (AI), and machine learning (ML) has resulted in a paradigm change in the manner in which novel medications are generated and healthcare is given. It is vital to systematically harness data from varied sources and utilize digital technologies and sophisticated analytics in order to allow data-driven decision making in order to fully capitalize on the breakthroughs in technology that have been made in recent years. The field of data science is now in a position where it has an unparalleled chance to steer such a paradigm shift. This book provides a high-level overview of fundamental concepts in algorithmic theory, data representation techniques, and generative modelling. Use the discovery of antibiotics as a case study in machine learning applied to the production of drugs, and then examine several applications in drug-likeness prediction, antimicrobial resistance, & avenues for further investigation. In the most recent years, there has been a marked increase in the application of machine learning algorithms to the process of drug discovery, and this book offers a comprehensive overview of the rapidly developing field. An introduction to the ways in which machine learning iv and artificial intelligence are being used in the pharmaceutical industry. The introductory discussion focuses on the use of machine learning to better understand medication-target interactions as a means of enhancing drug delivery as well as healthcare and medical systems. In addition to this, give subjects on medication repurposing using machine learning, drug designing, and finally, address drug combinations that are recommended to patients who have several or complicated diseases.

Artificial Intelligence in Drug Design

Author : Alexander Heifetz
Publisher :
ISBN 13 : 9781071617878
Total Pages : 529 pages
Book Rating : 4.6/5 (178 download)

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Book Synopsis Artificial Intelligence in Drug Design by : Alexander Heifetz

Download or read book Artificial Intelligence in Drug Design written by Alexander Heifetz and published by . This book was released on 2021 with total page 529 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume looks at applications of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in drug design. The chapters in this book describe how AI/ML/DL approaches can be applied to accelerate and revolutionize traditional drug design approaches such as: structure- and ligand-based, augmented and multi-objective de novo drug design, SAR and big data analysis, prediction of binding/activity, ADMET, pharmacokinetics and drug-target residence time, precision medicine and selection of favorable chemical synthetic routes. How broadly are these approaches applied and where do they maximally impact productivity today and potentially in the near future. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary software and tools, step-by-step, readily reproducible modeling protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and unique, Artificial Intelligence in Drug Design is a valuable resource for structural and molecular biologists, computational and medicinal chemists, pharmacologists and drug designers.

Artificial intelligence for Drug Discovery and Development

Author : Jianfeng Pei
Publisher : Frontiers Media SA
ISBN 13 : 288971649X
Total Pages : 229 pages
Book Rating : 4.8/5 (897 download)

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Book Synopsis Artificial intelligence for Drug Discovery and Development by : Jianfeng Pei

Download or read book Artificial intelligence for Drug Discovery and Development written by Jianfeng Pei and published by Frontiers Media SA. This book was released on 2021-11-16 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: Topic editor Alex Zhavoronkov is the founder of Insilico Medicine, a company specializing in AI research. He is also a professor at the Buck Institute for Research on Aging. All other Topic Editors declare no competing interests with regards to the Research Topic subject.

Artificial Intelligence in Oncology Drug Discovery and Development

Author : John Cassidy
Publisher : BoD – Books on Demand
ISBN 13 : 1789846897
Total Pages : 194 pages
Book Rating : 4.7/5 (898 download)

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Book Synopsis Artificial Intelligence in Oncology Drug Discovery and Development by : John Cassidy

Download or read book Artificial Intelligence in Oncology Drug Discovery and Development written by John Cassidy and published by BoD – Books on Demand. This book was released on 2020-09-09 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: There exists a profound conflict at the heart of oncology drug development. The efficiency of the drug development process is falling, leading to higher costs per approved drug, at the same time personalised medicine is limiting the target market of each new medicine. Even as the global economic burden of cancer increases, the current paradigm in drug development is unsustainable. In this book, we discuss the development of techniques in machine learning for improving the efficiency of oncology drug development and delivering cost-effective precision treatment. We consider how to structure data for drug repurposing and target identification, how to improve clinical trials and how patients may view artificial intelligence.

Machine Learning for Drug Discovery

Author : Marcelo C. R. Melo
Publisher : American Chemical Society
ISBN 13 : 0841299234
Total Pages : 218 pages
Book Rating : 4.8/5 (412 download)

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Book Synopsis Machine Learning for Drug Discovery by : Marcelo C. R. Melo

Download or read book Machine Learning for Drug Discovery written by Marcelo C. R. Melo and published by American Chemical Society. This book was released on 2022-03-11 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning for Drug Discovery is designed to suit the needs of graduate students, advanced undergraduates, chemists or biologists otherwise new to this research domain with minimal previous exposure to Machine Learning (ML) methods, or computational scientists with minimal exposure to medicinal chemistry. The e-book covers basic algorithmic theory, data representation methods, and generative modeling at a high level. The authors spotlight antibiotic discovery as a case study in ML for drug development and discuss diverse applications in drug-likeness prediction, antimicrobial resistance, and areas for future inquiry. For a more dynamic learning experience, open-source code demonstrations in Python are included.

Drug Design using Machine Learning

Author : Inamuddin
Publisher : John Wiley & Sons
ISBN 13 : 1394167237
Total Pages : 388 pages
Book Rating : 4.3/5 (941 download)

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Book Synopsis Drug Design using Machine Learning by : Inamuddin

Download or read book Drug Design using Machine Learning written by Inamuddin and published by John Wiley & Sons. This book was released on 2022-10-04 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: DRUG DESIGN USING MACHINE LEARNING The use of machine learning algorithms in drug discovery has accelerated in recent years and this book provides an in-depth overview of the still-evolving field. The objective of this book is to bring together several chapters that function as an overview of the use of machine learning and artificial intelligence applied to drug development. The initial chapters discuss drug-target interactions through machine learning for improving drug delivery, healthcare, and medical systems. Further chapters also provide topics on drug repurposing through machine learning, drug designing, and ultimately discuss drug combinations prescribed for patients with multiple or complex ailments. This excellent overview Provides a broad synopsis of machine learning and artificial intelligence applications to the advancement of drugs; Details the use of molecular recognition for drug development through various mathematical models; Highlights classical as well as machine learning-based approaches to study target-drug interactions in the field of drug discovery; Explores computer-aided technics for prediction of drug effectiveness and toxicity. Audience The book will be useful for information technology professionals, pharmaceutical industry workers, engineers, university researchers, medical practitioners, and laboratory workers who have a keen interest in the area of machine learning and artificial intelligence approaches applied to drug advancements.

Artificial intelligence in Pharmaceutical Sciences

Author : Mullaicharam Bhupathyraaj
Publisher : CRC Press
ISBN 13 : 1000994597
Total Pages : 265 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Artificial intelligence in Pharmaceutical Sciences by : Mullaicharam Bhupathyraaj

Download or read book Artificial intelligence in Pharmaceutical Sciences written by Mullaicharam Bhupathyraaj and published by CRC Press. This book was released on 2023-11-23 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: This cutting-edge reference book discusses the intervention of artificial intelligence in the fields of drug development, modified drug delivery systems, pharmaceutical technology, and medical devices development. This comprehensive book includes an overview of artificial intelligence in pharmaceutical sciences and applications in the drug discovery and development process. It discusses the role of machine learning in the automated detection and sorting of pharmaceutical formulations. It covers nanosafety and the role of artificial intelligence in predicting potential adverse biological effects. FEATURES Includes lucid, step-by-step instructions to apply artificial intelligence and machine learning in pharmaceutical sciences Explores the application of artificial intelligence in nanosafety and prediction of potential hazards Covers application of artificial intelligence in drug discovery and drug development Reviews the role of artificial intelligence in assessment of pharmaceutical formulations Provides artificial intelligence solutions for experts in the pharmaceutical and medical devices industries This book is meant for academicians, students, and industry experts in pharmaceutical sciences, medicine, and pharmacology.

Artificial Intelligence in Healthcare

Author : Adam Bohr
Publisher : Academic Press
ISBN 13 : 0128184396
Total Pages : 385 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Artificial Intelligence in Healthcare by : Adam Bohr

Download or read book Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

Artificial Intelligence in Drug Design

Author : Alexander Heifetz
Publisher : Humana
ISBN 13 : 9781071617892
Total Pages : 0 pages
Book Rating : 4.6/5 (178 download)

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Book Synopsis Artificial Intelligence in Drug Design by : Alexander Heifetz

Download or read book Artificial Intelligence in Drug Design written by Alexander Heifetz and published by Humana. This book was released on 2022-11-05 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume looks at applications of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in drug design. The chapters in this book describe how AI/ML/DL approaches can be applied to accelerate and revolutionize traditional drug design approaches such as: structure- and ligand-based, augmented and multi-objective de novo drug design, SAR and big data analysis, prediction of binding/activity, ADMET, pharmacokinetics and drug-target residence time, precision medicine and selection of favorable chemical synthetic routes. How broadly are these approaches applied and where do they maximally impact productivity today and potentially in the near future. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary software and tools, step-by-step, readily reproducible modeling protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and unique, Artificial Intelligence in Drug Design is a valuable resource for structural and molecular biologists, computational and medicinal chemists, pharmacologists and drug designers.

Deep Learning for the Life Sciences

Author : Bharath Ramsundar
Publisher : O'Reilly Media
ISBN 13 : 1492039802
Total Pages : 236 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Deep Learning for the Life Sciences by : Bharath Ramsundar

Download or read book Deep Learning for the Life Sciences written by Bharath Ramsundar and published by O'Reilly Media. This book was released on 2019-04-10 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning has already achieved remarkable results in many fields. Now it’s making waves throughout the sciences broadly and the life sciences in particular. This practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields. Ideal for practicing developers and scientists ready to apply their skills to scientific applications such as biology, genetics, and drug discovery, this book introduces several deep network primitives. You’ll follow a case study on the problem of designing new therapeutics that ties together physics, chemistry, biology, and medicine—an example that represents one of science’s greatest challenges. Learn the basics of performing machine learning on molecular data Understand why deep learning is a powerful tool for genetics and genomics Apply deep learning to understand biophysical systems Get a brief introduction to machine learning with DeepChem Use deep learning to analyze microscopic images Analyze medical scans using deep learning techniques Learn about variational autoencoders and generative adversarial networks Interpret what your model is doing and how it’s working

Artificial Intelligence in Drug Discovery

Author : Ankit Gangwal
Publisher : Independently Published
ISBN 13 :
Total Pages : 358 pages
Book Rating : 4.7/5 (186 download)

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Book Synopsis Artificial Intelligence in Drug Discovery by : Ankit Gangwal

Download or read book Artificial Intelligence in Drug Discovery written by Ankit Gangwal and published by Independently Published. This book was released on 2021-03-08 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Major disruption worldover is due to AI, blockchain, 3D organ printing and others. Almost all the industries are being affected by AI. Health sector, particularly pharmaceutical sciences is also not an exception. The book has been designed to cover basics and role of AI in drug discovery, including clinical trials and other departments of health and pharmaceutical sciences. All the content has been compiled after referring and mining hundreds of latest and original first-hand updates from inventors, experts, organizations (who/which are engaged in drug discovery research directly or indirectly through AI) like Insilico, Google, Microsoft, INVIDIA, Novartis, Intel, IBM, Exscientia, Berg, Atomwise, XtalPi, Recursion, H2OAi, Recursion, BenevolentAI, Minds.ai, Deep Genomics, AiCure, Trials.ai, GNS Healthcare, MIT, Okwin, Flatiron, Syapse etc. It was unavoidable to explore content from websites and newspapers as authors were interested to cover latest content. All topics are explained in very simple language with clear aim and outcome using flow charts, tables and infographics. Professionals from medical, pharmacy, nursing and dental and medical imaging arena will find this book very useful. Students of all levels will find book very beneficial as few topics have been just touched, few have been shallow in complexity and rest are covered in detail. Full precautions have been exercised to address the needs of pharmacy students so that they can easily and effortlessly understand the subject matter of this book. Recent examples from various corporates, universities and daily life have found place in this unique book in a very explicit manner. At the end, questions have been added for the readers, mainly students. Authors are always open to suggestions, comments from our valuable readers. We wish you a happy reading......

Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications

Author : Om Prakash Jena
Publisher : CRC Press
ISBN 13 : 1000533972
Total Pages : 332 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications by : Om Prakash Jena

Download or read book Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications written by Om Prakash Jena and published by CRC Press. This book was released on 2022-02-25 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications introduces and explores a variety of schemes designed to empower, enhance, and represent multi-institutional and multi-disciplinary machine learning (ML) and deep learning (DL) research in healthcare paradigms. Serving as a unique compendium of existing and emerging ML/DL paradigms for the healthcare sector, this book demonstrates the depth, breadth, complexity, and diversity of this multi-disciplinary area. It provides a comprehensive overview of ML/DL algorithms and explores the related use cases in enterprises such as computer-aided medical diagnostics, drug discovery and development, medical imaging, automation, robotic surgery, electronic smart records creation, outbreak prediction, medical image analysis, and radiation treatments. This book aims to endow different communities with the innovative advances in theory, analytical results, case studies, numerical simulation, modeling, and computational structuring in the field of ML/DL models for healthcare applications. It will reveal different dimensions of ML/DL applications and will illustrate their use in the solution of assorted real-world biomedical and healthcare problems. Features: Covers the fundamentals of ML and DL in the context of healthcare applications Discusses various data collection approaches from various sources and how to use them in ML/DL models Integrates several aspects of AI-based computational intelligence such as ML and DL from diversified perspectives which describe recent research trends and advanced topics in the field Explores the current and future impacts of pandemics and risk mitigation in healthcare with advanced analytics Emphasizes feature selection as an important step in any accurate model simulation where ML/DL methods are used to help train the system and extract the positive solution implicitly This book is a valuable source of information for researchers, scientists, healthcare professionals, programmers, and graduate-level students interested in understanding the applications of ML/DL in healthcare scenarios. Dr. Om Prakash Jena is an Assistant Professor in the Department of Computer Science, Ravenshaw University, Cuttack, Odisha, India. Dr. Bharat Bhushan is an Assistant Professor of Department of Computer Science and Engineering (CSE) at the School of Engineering and Technology, Sharda University, Greater Noida, India. Dr. Utku Kose is an Associate Professor in Suleyman Demirel University, Turkey.