Target Discovery for Anticancer Therapy Facilitated by Artificial Intelligence
Author | : Feng Zhu |
Publisher | : Frontiers Media SA |
Total Pages | : 218 |
Release | : 2021-08-19 |
Genre | : Science |
ISBN | : 2889712001 |
Download Target Discovery For Anticancer Therapy Facilitated By Artificial Intelligence full books in PDF, epub, and Kindle. Read online free Target Discovery For Anticancer Therapy Facilitated By Artificial Intelligence ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Author | : Feng Zhu |
Publisher | : Frontiers Media SA |
Total Pages | : 218 |
Release | : 2021-08-19 |
Genre | : Science |
ISBN | : 2889712001 |
Author | : Nathan Brown |
Publisher | : Royal Society of Chemistry |
Total Pages | : 425 |
Release | : 2020-11-04 |
Genre | : Computers |
ISBN | : 1839160543 |
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.
Author | : Adam Bohr |
Publisher | : Academic Press |
Total Pages | : 385 |
Release | : 2020-06-21 |
Genre | : Computers |
ISBN | : 0128184396 |
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
Author | : Quentin Vanhaelen |
Publisher | : Humana |
Total Pages | : 0 |
Release | : 2018-12-14 |
Genre | : Medical |
ISBN | : 9781493989546 |
This detailed book explores techniques commonly used for research into drug repurposing, a well-known strategy to find alternative indications for drugs which have already undergone toxicology and pharma-kinetic studies but have failed later stages during the development, via computational methods. Thereby, it addresses the intense challenges of identifying the appropriate type of algorithm and relevant technical information for computational repurposing. Written for the highly successful Methods in Molecular Biology series, the authors of each chapter use their experience in the field to describe the implementation and successful use of a specific repurposing method thus providing lab-ready instruction. Authoritative and practical, Computational Methods for Drug Repurposing serves as an ideal guide to researchers interested in this vital area of drug development.
Author | : Alexander Heifetz |
Publisher | : Humana |
Total Pages | : 0 |
Release | : 2022-11-05 |
Genre | : Medical |
ISBN | : 9781071617892 |
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.
Author | : Gisbert Schneider |
Publisher | : John Wiley & Sons |
Total Pages | : 540 |
Release | : 2013-10-10 |
Genre | : Medical |
ISBN | : 3527677038 |
Systematically examining current methods and strategies, this ready reference covers a wide range of molecular structures, from organic-chemical drugs to peptides, Proteins and nucleic acids, in line with emerging new drug classes derived from biomacromolecules. A leader in the field and one of the pioneers of this young discipline has assembled here the most prominent experts from across the world to provide first-hand knowledge. While most of their methods and examples come from the area of pharmaceutical discovery and development, the approaches are equally applicable for chemical probes and diagnostics, pesticides, and any other molecule designed to interact with a biological system. Numerous images and screenshots illustrate the many examples and method descriptions. With its broad and balanced coverage, this will be the firststop resource not only for medicinal chemists, biochemists and biotechnologists, but equally for bioinformaticians and molecular designers for many years to come. From the content: * Reaction-driven de novo design * Adaptive methods in molecular design * Design of ligands against multitarget profiles * Free energy methods in ligand design * Fragment-based de novo design * Automated design of focused and target family-oriented compound libraries * Molecular de novo design by nature-inspired computing * 3D QSAR approaches to de novo drug design * Bioisosteres in de novo design * De novo design of peptides, proteins and nucleic acid structures, including RNA aptamers and many more.
Author | : Bharath Ramsundar |
Publisher | : O'Reilly Media |
Total Pages | : 236 |
Release | : 2019-04-10 |
Genre | : Science |
ISBN | : 1492039802 |
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
Author | : Jaber, Wassim |
Publisher | : IGI Global |
Total Pages | : 313 |
Release | : 2023-12-07 |
Genre | : Technology & Engineering |
ISBN | : |
In the world of academia, scholars and researchers are confronted with a rapidly expanding knowledge base in Artificial Intelligence (AI) and nanotechnology. The integration of these two groundbreaking fields presents an intricate web of concepts, innovations, and interdisciplinary applications that can overwhelm even the most astute academic minds. Staying up to date with the latest developments and effectively navigating this complex terrain has become a pressing challenge for those striving to contribute meaningfully to these fields. Artificial Intelligence in the Age of Nanotechnology is a transformative solution meticulously crafted to address the academic community's knowledge gaps and challenges. This comprehensive book serves as the guiding light for scholars, researchers, and students grappling with the dynamic synergy between AI and Nanotechnology. It offers a structured and authoritative exploration of the core principles and transformative applications of these domains across diverse fields. By providing clarity and depth, it empowers academics to stay at the forefront of innovation and make informed contributions.
Author | : Chad Brenner |
Publisher | : MDPI |
Total Pages | : 418 |
Release | : 2019-11-20 |
Genre | : Medical |
ISBN | : 3039217887 |
This collection of 25 research papers comprised of 22 original articles and 3 reviews is brought together from international leaders in bioinformatics and biostatistics. The collection highlights recent computational advances that improve the ability to analyze highly complex data sets to identify factors critical to cancer biology. Novel deep learning algorithms represent an emerging and highly valuable approach for collecting, characterizing and predicting clinical outcomes data. The collection highlights several of these approaches that are likely to become the foundation of research and clinical practice in the future. In fact, many of these technologies reveal new insights about basic cancer mechanisms by integrating data sets and structures that were previously immiscible. Accordingly, the series presented here bring forward a wide range of artificial intelligence approaches and statistical methods that can be applied to imaging and genomics data sets to identify previously unrecognized features that are critical for cancer. Our hope is that these articles will serve as a foundation for future research as the field of cancer biology transitions to integrating electronic health record, imaging, genomics and other complex datasets in order to develop new strategies that improve the overall health of individual patients.
Author | : Diane Purchase |
Publisher | : Springer |
Total Pages | : 407 |
Release | : 2016-09-13 |
Genre | : Science |
ISBN | : 3319428527 |
Fungi are distinct eukaryotic organisms renowned for their remarkable biodiversity and extensive habitat range. Many fungal species have long been exploited for food and medicines. This volume considers other important applications of fungal biotechnology especially in an environmental context, showcasing the essential contributions of these amazingly versatile organisms. It explores how fungi offer sustainable solutions to tackle various environmental concerns. Written by eminent experts in their fields, this work presents a broad array of current advances and future prospects in fungal environmental biotechnology and discusses their limitations and potential. The book is organized in five parts, each addressing a theme of the UN Sustainable Development Goals (SDG): strengthen food security (Zero Hunger), wastewater treatment (Clean Water & Sanitation), pollution reduction (Life on Land), biofuel production (Affordable & Clean Energy) and biosynthesis of novel biomolecules (Responsible Consumption & Production).