Machine Learning In Biotechnology And Life Sciences

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Machine Learning in Biotechnology and Life Sciences

Saleh Alkhalifa
Machine Learning in Biotechnology and Life Sciences Book PDF

Author : Saleh Alkhalifa
Publisher : Packt Publishing Ltd
Page : 408 pages
File Size : 42,7 Mb
Release : 2022-01-28
Category : Mathematics
ISBN : 9781801815673

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Machine Learning in Biotechnology and Life Sciences by Saleh Alkhalifa Pdf

Explore all the tools and templates needed for data scientists to drive success in their biotechnology careers with this comprehensive guide Key FeaturesLearn the applications of machine learning in biotechnology and life science sectorsDiscover exciting real-world applications of deep learning and natural language processingUnderstand the general process of deploying models to cloud platforms such as AWS and GCPBook Description The booming fields of biotechnology and life sciences have seen drastic changes over the last few years. With competition growing in every corner, companies around the globe are looking to data-driven methods such as machine learning to optimize processes and reduce costs. This book helps lab scientists, engineers, and managers to develop a data scientist's mindset by taking a hands-on approach to learning about the applications of machine learning to increase productivity and efficiency in no time. You'll start with a crash course in Python, SQL, and data science to develop and tune sophisticated models from scratch to automate processes and make predictions in the biotechnology and life sciences domain. As you advance, the book covers a number of advanced techniques in machine learning, deep learning, and natural language processing using real-world data. By the end of this machine learning book, you'll be able to build and deploy your own machine learning models to automate processes and make predictions using AWS and GCP. What you will learnGet started with Python programming and Structured Query Language (SQL)Develop a machine learning predictive model from scratch using PythonFine-tune deep learning models to optimize their performance for various tasksFind out how to deploy, evaluate, and monitor a model in the cloudUnderstand how to apply advanced techniques to real-world dataDiscover how to use key deep learning methods such as LSTMs and transformersWho this book is for This book is for data scientists and scientific professionals looking to transcend to the biotechnology domain. Scientific professionals who are already established within the pharmaceutical and biotechnology sectors will find this book useful. A basic understanding of Python programming and beginner-level background in data science conjunction is needed to get the most out of this book.

Machine Learning in Biological Sciences

Shyamasree Ghosh,Rathi Dasgupta
Machine Learning in Biological Sciences Book PDF

Author : Shyamasree Ghosh,Rathi Dasgupta
Publisher : Springer Nature
Page : 337 pages
File Size : 43,5 Mb
Release : 2022-05-04
Category : Medical
ISBN : 9789811688812

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Machine Learning in Biological Sciences by Shyamasree Ghosh,Rathi Dasgupta Pdf

This book gives an overview of applications of Machine Learning (ML) in diverse fields of biological sciences, including healthcare, animal sciences, agriculture, and plant sciences. Machine learning has major applications in process modelling, computer vision, signal processing, speech recognition, and language understanding and processing and life, and health sciences. It is increasingly used in understanding DNA patterns and in precision medicine. This book is divided into eight major sections, each containing chapters that describe the application of ML in a certain field. The book begins by giving an introduction to ML and the various ML methods. It then covers interesting and timely aspects such as applications in genetics, cell biology, the study of plant-pathogen interactions, and animal behavior. The book discusses computational methods for toxicity prediction of environmental chemicals and drugs, which forms a major domain of research in the field of biology. It is of relevance to post-graduate students and researchers interested in exploring the interdisciplinary areas of use of machine learning and deep learning in life sciences.

Deep Learning for the Life Sciences

Bharath Ramsundar,Peter Eastman,Patrick Walters,Vijay Pande
Deep Learning for the Life Sciences Book PDF

Author : Bharath Ramsundar,Peter Eastman,Patrick Walters,Vijay Pande
Publisher : O'Reilly Media
Page : 236 pages
File Size : 45,7 Mb
Release : 2019-04-10
Category : Science
ISBN : 9781492039808

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Deep Learning for the Life Sciences by Bharath Ramsundar,Peter Eastman,Patrick Walters,Vijay Pande Pdf

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

Deep Learning for the Life Sciences

Bharath Ramsundar,Peter Eastman,Patrick Walters,Vijay Pande
Deep Learning for the Life Sciences Book PDF

Author : Bharath Ramsundar,Peter Eastman,Patrick Walters,Vijay Pande
Publisher : "O'Reilly Media, Inc."
Page : 244 pages
File Size : 47,8 Mb
Release : 2019-04-10
Category : Science
ISBN : 9781492039785

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Deep Learning for the Life Sciences by Bharath Ramsundar,Peter Eastman,Patrick Walters,Vijay Pande Pdf

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

Deep Learning In Biology And Medicine

Davide Bacciu,Paulo J G Lisboa,Alfredo Vellido
Deep Learning In Biology And Medicine Book PDF

Author : Davide Bacciu,Paulo J G Lisboa,Alfredo Vellido
Publisher : World Scientific
Page : 333 pages
File Size : 55,8 Mb
Release : 2022-01-17
Category : Computers
ISBN : 9781800610958

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Deep Learning In Biology And Medicine by Davide Bacciu,Paulo J G Lisboa,Alfredo Vellido Pdf

Biology, medicine and biochemistry have become data-centric fields for which Deep Learning methods are delivering groundbreaking results. Addressing high impact challenges, Deep Learning in Biology and Medicine provides an accessible and organic collection of Deep Learning essays on bioinformatics and medicine. It caters for a wide readership, ranging from machine learning practitioners and data scientists seeking methodological knowledge to address biomedical applications, to life science specialists in search of a gentle reference for advanced data analytics.With contributions from internationally renowned experts, the book covers foundational methodologies in a wide spectrum of life sciences applications, including electronic health record processing, diagnostic imaging, text processing, as well as omics-data processing. This survey of consolidated problems is complemented by a selection of advanced applications, including cheminformatics and biomedical interaction network analysis. A modern and mindful approach to the use of data-driven methodologies in the life sciences also requires careful consideration of the associated societal, ethical, legal and transparency challenges, which are covered in the concluding chapters of this book.

Applied Machine Learning for Healthcare and Life Sciences Using AWS

Ujjwal Ratan
Applied Machine Learning for Healthcare and Life Sciences Using AWS Book PDF

Author : Ujjwal Ratan
Publisher : Packt Publishing Ltd
Page : 224 pages
File Size : 54,6 Mb
Release : 2022-11-25
Category : Computers
ISBN : 9781804619193

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Applied Machine Learning for Healthcare and Life Sciences Using AWS by Ujjwal Ratan Pdf

Build real-world artificial intelligence apps on AWS to overcome challenges faced by healthcare providers and payers, as well as pharmaceutical, life sciences research, and commercial organizations Key FeaturesLearn about healthcare industry challenges and how machine learning can solve themExplore AWS machine learning services and their applications in healthcare and life sciencesDiscover practical coding instructions to implement machine learning for healthcare and life sciencesBook Description While machine learning is not new, it's only now that we are beginning to uncover its true potential in the healthcare and life sciences industry. The availability of real-world datasets and access to better compute resources have helped researchers invent applications that utilize known AI techniques in every segment of this industry, such as providers, payers, drug discovery, and genomics. This book starts by summarizing the introductory concepts of machine learning and AWS machine learning services. You'll then go through chapters dedicated to each segment of the healthcare and life sciences industry. Each of these chapters has three key purposes -- First, to introduce each segment of the industry, its challenges, and the applications of machine learning relevant to that segment. Second, to help you get to grips with the features of the services available in the AWS machine learning stack like Amazon SageMaker and Amazon Comprehend Medical. Third, to enable you to apply your new skills to create an ML-driven solution to solve problems particular to that segment. The concluding chapters outline future industry trends and applications. By the end of this book, you'll be aware of key challenges faced in applying AI to healthcare and life sciences industry and learn how to address those challenges with confidence. What you will learnExplore the healthcare and life sciences industryFind out about the key applications of AI in different industry segmentsApply AI to medical images, clinical notes, and patient dataDiscover security, privacy, fairness, and explainability best practicesExplore the AWS ML stack and key AI services for the industryDevelop practical ML skills using code and AWS servicesDiscover all about industry regulatory requirementsWho this book is for This book is specifically tailored toward technology decision-makers, data scientists, machine learning engineers, and anyone who works in the data engineering role in healthcare and life sciences organizations. Whether you want to apply machine learning to overcome common challenges in the healthcare and life science industry or are looking to understand the broader industry AI trends and landscape, this book is for you. This book is filled with hands-on examples for you to try as you learn about new AWS AI concepts.

Applications of Machine Learning and Deep Learning on Biological Data

Faheem Masoodi,Mohammad Quasim,Syed Bukhari,Sarvottam Dixit,Shadab Alam
Applications of Machine Learning and Deep Learning on Biological Data Book PDF

Author : Faheem Masoodi,Mohammad Quasim,Syed Bukhari,Sarvottam Dixit,Shadab Alam
Publisher : CRC Press
Page : 211 pages
File Size : 55,7 Mb
Release : 2023-03-13
Category : Computers
ISBN : 9781000833768

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Applications of Machine Learning and Deep Learning on Biological Data by Faheem Masoodi,Mohammad Quasim,Syed Bukhari,Sarvottam Dixit,Shadab Alam Pdf

Unique selling point: Advanced AI solutions for problems in genetics, virology, and related areas of life science Core audience: Researchers in bioinformatics Place in the market: High-level reference book on advanced applied technology

Artificial Intelligence in Healthcare

Adam Bohr,Kaveh Memarzadeh
Artificial Intelligence in Healthcare Book PDF

Author : Adam Bohr,Kaveh Memarzadeh
Publisher : Academic Press
Page : 385 pages
File Size : 49,8 Mb
Release : 2020-06-21
Category : Computers
ISBN : 9780128184394

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Artificial Intelligence in Healthcare by Adam Bohr,Kaveh Memarzadeh Pdf

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

Machine Learning

Mr. Y. David Solomon Raju, M. Tech, (Ph. D.), LMISTE, LMISOI, FIETE, MIE, MIAENG, Associate Professor, Department of Electronics and Communication Engineering, Holy Mary Institute of Technology & Science (AUTONOMOUS) ,Mrs. K. Shyamala Assistant Professor, Department of Electronics and Communication Engineering, Holy Mary Institute of Technology & Science (AUTONOMOUS) ,Mrs. Ch. Sumalatha Assistant Professor, Dept. of Electronics and Communication Engineering, Shadan Women's College of Engineering & Technology, Hyderabad,
Machine Learning Book PDF

Author : Mr. Y. David Solomon Raju, M. Tech, (Ph. D.), LMISTE, LMISOI, FIETE, MIE, MIAENG, Associate Professor, Department of Electronics and Communication Engineering, Holy Mary Institute of Technology & Science (AUTONOMOUS) ,Mrs. K. Shyamala Assistant Professor, Department of Electronics and Communication Engineering, Holy Mary Institute of Technology & Science (AUTONOMOUS) ,Mrs. Ch. Sumalatha Assistant Professor, Dept. of Electronics and Communication Engineering, Shadan Women's College of Engineering & Technology, Hyderabad,
Publisher : GCS PUBLISHERS
Page : 128 pages
File Size : 54,6 Mb
Release : 2024-05-27
Category : Antiques & Collectibles
ISBN : 9789394304253

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Machine Learning by Mr. Y. David Solomon Raju, M. Tech, (Ph. D.), LMISTE, LMISOI, FIETE, MIE, MIAENG, Associate Professor, Department of Electronics and Communication Engineering, Holy Mary Institute of Technology & Science (AUTONOMOUS) ,Mrs. K. Shyamala Assistant Professor, Department of Electronics and Communication Engineering, Holy Mary Institute of Technology & Science (AUTONOMOUS) ,Mrs. Ch. Sumalatha Assistant Professor, Dept. of Electronics and Communication Engineering, Shadan Women's College of Engineering & Technology, Hyderabad, Pdf

Machine Learning WRITTEN BY Y. David Solomon Raju, K. Shyamala, Ch. Sumalatha

Machine Learning and IoT

Shampa Sen,Leonid Datta,Sayak Mitra
Machine Learning and IoT Book PDF

Author : Shampa Sen,Leonid Datta,Sayak Mitra
Publisher : CRC Press
Page : 397 pages
File Size : 46,8 Mb
Release : 2018-07-04
Category : Computers
ISBN : 9781351029926

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Machine Learning and IoT by Shampa Sen,Leonid Datta,Sayak Mitra Pdf

This book discusses some of the innumerable ways in which computational methods can be used to facilitate research in biology and medicine - from storing enormous amounts of biological data to solving complex biological problems and enhancing treatment of various grave diseases.

PlantOmics: The Omics of Plant Science

Debmalya Barh,Muhammad Sarwar Khan,Eric Davies
PlantOmics The Omics of Plant Science Book PDF

Author : Debmalya Barh,Muhammad Sarwar Khan,Eric Davies
Publisher : Springer
Page : 825 pages
File Size : 54,6 Mb
Release : 2015-03-18
Category : Science
ISBN : 9788132221722

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PlantOmics: The Omics of Plant Science by Debmalya Barh,Muhammad Sarwar Khan,Eric Davies Pdf

PlantOmics: The Omics of Plant Science provides a comprehensive account of the latest trends and developments of omics technologies or approaches and their applications in plant science. Thirty chapters written by 90 experts from 15 countries are included in this state-of-the-art book. Each chapter describes one topic/omics such as: omics in model plants, spectroscopy for plants, next generation sequencing, functional genomics, cyto-metagenomics, epigenomics, miRNAomics, proteomics, metabolomics, glycomics, lipidomics, secretomics, phenomics, cytomics, physiomics, signalomics, thiolomics, organelle omics, micro morphomics, microbiomics, cryobionomics, nanotechnology, pharmacogenomics, and computational systems biology for plants. It provides up to date information, technologies, and their applications that can be adopted and applied easily for deeper understanding plant biology and therefore will be helpful in developing the strategy for generating cost-effective superior plants for various purposes. In the last chapter, the editors have proposed several new areas in plant omics that may be explored in order to develop an integrated meta-omics strategy to ensure the world and earth’s health and related issues. This book will be a valuable resource to students and researchers in the field of cutting-edge plant omics.

Applied Machine Learning for Healthcare and Life Sciences Using AWS

Ujjwal Ratan
Applied Machine Learning for Healthcare and Life Sciences Using AWS Book PDF

Author : Ujjwal Ratan
Publisher : Packt Publishing
Page : 0 pages
File Size : 43,5 Mb
Release : 2022-11-25
Category : Electronic
ISBN : 1804610216

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Applied Machine Learning for Healthcare and Life Sciences Using AWS by Ujjwal Ratan Pdf

Build real-world artificial intelligence apps on AWS to overcome challenges faced by healthcare providers and payers, as well as pharmaceutical, life sciences research, and commercial organizations Key Features: Learn about healthcare industry challenges and how machine learning can solve them Explore AWS machine learning services and their applications in healthcare and life sciences Discover practical coding instructions to implement machine learning for healthcare and life sciences Book Description: While machine learning is not new, it's only now that we are beginning to uncover its true potential in the healthcare and life sciences industry. The availability of real-world datasets and access to better compute resources have helped researchers invent applications that utilize known AI techniques in every segment of this industry, such as providers, payers, drug discovery, and genomics. This book starts by summarizing the introductory concepts of machine learning and AWS machine learning services. You'll then go through chapters dedicated to each segment of the healthcare and life sciences industry. Each of these chapters has three key purposes -- First, to introduce each segment of the industry, its challenges, and the applications of machine learning relevant to that segment. Second, to help you get to grips with the features of the services available in the AWS machine learning stack like Amazon SageMaker and Amazon Comprehend Medical. Third, to enable you to apply your new skills to create an ML-driven solution to solve problems particular to that segment. The concluding chapters outline future industry trends and applications. By the end of this book, you'll be aware of key challenges faced in applying AI to healthcare and life sciences industry and learn how to address those challenges with confidence. What You Will Learn: Explore the healthcare and life sciences industry Find out about the key applications of AI in different industry segments Apply AI to medical images, clinical notes, and patient data Discover security, privacy, fairness, and explainability best practices Explore the AWS ML stack and key AI services for the industry Develop practical ML skills using code and AWS services Discover all about industry regulatory requirements Who this book is for: This book is specifically tailored toward technology decision-makers, data scientists, machine learning engineers, and anyone who works in the data engineering role in healthcare and life sciences organizations. Whether you want to apply machine learning to overcome common challenges in the healthcare and life science industry or are looking to understand the broader industry AI trends and landscape, this book is for you. This book is filled with hands-on examples for you to try as you learn about new AWS AI concepts.

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

Stephanie K. Ashenden
The Era of Artificial Intelligence Machine Learning and Data Science in the Pharmaceutical Industry Book PDF

Author : Stephanie K. Ashenden
Publisher : Academic Press
Page : 266 pages
File Size : 48,8 Mb
Release : 2021-04-23
Category : Computers
ISBN : 9780128204498

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

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

Biodefense in the Age of Synthetic Biology

National Academies of Sciences, Engineering, and Medicine,Division on Earth and Life Studies,Board on Life Sciences,Board on Chemical Sciences and Technology,Committee on Strategies for Identifying and Addressing Potential Biodefense Vulnerabilities Posed by Synthetic Biology
Biodefense in the Age of Synthetic Biology Book PDF

Author : National Academies of Sciences, Engineering, and Medicine,Division on Earth and Life Studies,Board on Life Sciences,Board on Chemical Sciences and Technology,Committee on Strategies for Identifying and Addressing Potential Biodefense Vulnerabilities Posed by Synthetic Biology
Publisher : National Academies Press
Page : 189 pages
File Size : 45,6 Mb
Release : 2019-01-05
Category : Technology & Engineering
ISBN : 9780309465182

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Biodefense in the Age of Synthetic Biology by National Academies of Sciences, Engineering, and Medicine,Division on Earth and Life Studies,Board on Life Sciences,Board on Chemical Sciences and Technology,Committee on Strategies for Identifying and Addressing Potential Biodefense Vulnerabilities Posed by Synthetic Biology Pdf

Scientific advances over the past several decades have accelerated the ability to engineer existing organisms and to potentially create novel ones not found in nature. Synthetic biology, which collectively refers to concepts, approaches, and tools that enable the modification or creation of biological organisms, is being pursued overwhelmingly for beneficial purposes ranging from reducing the burden of disease to improving agricultural yields to remediating pollution. Although the contributions synthetic biology can make in these and other areas hold great promise, it is also possible to imagine malicious uses that could threaten U.S. citizens and military personnel. Making informed decisions about how to address such concerns requires a realistic assessment of the capabilities that could be misused. Biodefense in the Age of Synthetic Biology explores and envisions potential misuses of synthetic biology. This report develops a framework to guide an assessment of the security concerns related to advances in synthetic biology, assesses the levels of concern warranted for such advances, and identifies options that could help mitigate those concerns.

A Biologist’s Guide to Artificial Intelligence

Ambreen Hamadani,Nazir A Ganai,Hamadani Henna,J Bashir
A Biologist s Guide to Artificial Intelligence Book PDF

Author : Ambreen Hamadani,Nazir A Ganai,Hamadani Henna,J Bashir
Publisher : Elsevier
Page : 370 pages
File Size : 49,8 Mb
Release : 2024-03-15
Category : Computers
ISBN : 9780443240003

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A Biologist’s Guide to Artificial Intelligence by Ambreen Hamadani,Nazir A Ganai,Hamadani Henna,J Bashir Pdf

A Biologist’s Guide to Artificial Intelligence: Building the Foundations of Artificial Intelligence and Machine Learning for Achieving Advancements in Life Sciences provides an overview of the basics of Artificial Intelligence for life science biologists. In 14 chapters/sections, readers will find an introduction to Artificial Intelligence from a biologist’s perspective, including coverage of AI in precision medicine, disease detection, and drug development. The book also gives insights into the AI techniques used in biology and the applications of AI in food, and in environmental, evolutionary, agricultural, and bioinformatic sciences. Final chapters cover ethical issues surrounding AI and the impact of AI on the future. This book covers an interdisciplinary area and is therefore is an important subject matter resource and reference for researchers in biology and students pursuing their degrees in all areas of Life Sciences. It is also a useful title for the industry sector and computer scientists who would gain a better understanding of the needs and requirements of biological sciences and thus better tune the algorithms. Helps biologists succeed in understanding the concepts of Artificial Intelligence and machine learning Equips with new data mining strategies an easy interface into the world of Artificial Intelligence Enables researchers to enhance their own sphere of researching Artificial Intelligence