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Introduction To Machine Learning And Bioinformatics


Introduction To Machine Learning And Bioinformatics
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Introduction To Machine Learning And Bioinformatics


Introduction To Machine Learning And Bioinformatics
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Author : Sushmita Mitra
language : en
Publisher: CRC Press
Release Date : 2008-06-05

Introduction To Machine Learning And Bioinformatics written by Sushmita Mitra and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-06-05 with Business & Economics categories.


Lucidly Integrates Current Activities Focusing on both fundamentals and recent advances, Introduction to Machine Learning and Bioinformatics presents an informative and accessible account of the ways in which these two increasingly intertwined areas relate to each other. Examines Connections between Machine Learning & Bio



Introduction To Machine Learning


Introduction To Machine Learning
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Author : Ethem Alpaydin
language : en
Publisher: MIT Press
Release Date : 2004

Introduction To Machine Learning written by Ethem Alpaydin and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computers categories.


An introductory text in machine learning that gives a unified treatment of methods based on statistics, pattern recognition, neural networks, artificial intelligence, signal processing, control, and data mining.



A Guide To Applied Machine Learning For Biologists


A Guide To Applied Machine Learning For Biologists
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Author : Mohammad "Sufian" Badar
language : en
Publisher: Springer Nature
Release Date : 2023-06-21

A Guide To Applied Machine Learning For Biologists written by Mohammad "Sufian" Badar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-21 with Science categories.


This textbook is an introductory guide to applied machine learning, specifically for biology students. It familiarizes biology students with the basics of modern computer science and mathematics and emphasizes the real-world applications of these subjects. The chapters give an overview of computer systems and programming languages to establish a basic understanding of the important concepts in computer systems. Readers are introduced to machine learning and artificial intelligence in the field of bioinformatics, connecting these applications to systems biology, biological data analysis and predictions, and healthcare diagnosis and treatment. This book offers a necessary foundation for more advanced computer-based technologies used in biology, employing case studies, real-world issues, and various examples to guide the reader from the basic prerequisites to machine learning and its applications.



Machine Learning In Bioinformatics


Machine Learning In Bioinformatics
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Author : Yanqing Zhang
language : en
Publisher: John Wiley & Sons
Release Date : 2009-02-23

Machine Learning In Bioinformatics written by Yanqing Zhang and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-02-23 with Computers categories.


An introduction to machine learning methods and their applications to problems in bioinformatics Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. From an internationally recognized panel of prominent researchers in the field, Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics. Coverage includes: feature selection for genomic and proteomic data mining; comparing variable selection methods in gene selection and classification of microarray data; fuzzy gene mining; sequence-based prediction of residue-level properties in proteins; probabilistic methods for long-range features in biosequences; and much more. Machine Learning in Bioinformatics is an indispensable resource for computer scientists, engineers, biologists, mathematicians, researchers, clinicians, physicians, and medical informaticists. It is also a valuable reference text for computer science, engineering, and biology courses at the upper undergraduate and graduate levels.



Deep Learning Machine Learning And Iot In Biomedical And Health Informatics


Deep Learning Machine Learning And Iot In Biomedical And Health Informatics
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Author : Sujata Dash
language : en
Publisher: CRC Press
Release Date : 2022-02-10

Deep Learning Machine Learning And Iot In Biomedical And Health Informatics written by Sujata Dash and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-10 with Computers categories.


Biomedical and Health Informatics is an important field that brings tremendous opportunities and helps address challenges due to an abundance of available biomedical data. This book examines and demonstrates state-of-the-art approaches for IoT and Machine Learning based biomedical and health related applications. This book aims to provide computational methods for accumulating, updating and changing knowledge in intelligent systems and particularly learning mechanisms that help us to induce knowledge from the data. It is helpful in cases where direct algorithmic solutions are unavailable, there is lack of formal models, or the knowledge about the application domain is inadequately defined. In the future IoT has the impending capability to change the way we work and live. These computing methods also play a significant role in design and optimization in diverse engineering disciplines. With the influence and the development of the IoT concept, the need for AI (artificial intelligence) techniques has become more significant than ever. The aim of these techniques is to accept imprecision, uncertainties and approximations to get a rapid solution. However, recent advancements in representation of intelligent IoTsystems generate a more intelligent and robust system providing a human interpretable, low-cost, and approximate solution. Intelligent IoT systems have demonstrated great performance to a variety of areas including big data analytics, time series, biomedical and health informatics. This book will be very beneficial for the new researchers and practitioners working in the biomedical and healthcare fields to quickly know the best performing methods. It will also be suitable for a wide range of readers who may not be scientists but who are also interested in the practice of such areas as medical image retrieval, brain image segmentation, among others. • Discusses deep learning, IoT, machine learning, and biomedical data analysis with broad coverage of basic scientific applications • Presents deep learning and the tremendous improvement in accuracy, robustness, and cross- language generalizability it has over conventional approaches • Discusses various techniques of IoT systems for healthcare data analytics • Provides state-of-the-art methods of deep learning, machine learning and IoT in biomedical and health informatics • Focuses more on the application of algorithms in various real life biomedical and engineering problems



Original Strategies For Training And Educational Initiatives In Bioinformatics


Original Strategies For Training And Educational Initiatives In Bioinformatics
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Author : Hugo Verli
language : en
Publisher: Frontiers Media SA
Release Date : 2022-10-07

Original Strategies For Training And Educational Initiatives In Bioinformatics written by Hugo Verli and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-07 with Science categories.




The Hitchhiker S Guide To Machine Learning Algorithms


The Hitchhiker S Guide To Machine Learning Algorithms
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Author : Devin Schumacher
language : en
Publisher: SERP Media
Release Date : 2023-07-26

The Hitchhiker S Guide To Machine Learning Algorithms written by Devin Schumacher and has been published by SERP Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-26 with Computers categories.


Hello humans & welcome to the world of machines! Specifically, machine learning & algorithms. We are about to embark on an exciting adventure through the vast and varied landscape of algorithms that power the cutting-edge field of artificial intelligence. Machine learning is changing the world as we know it. From predicting stock market trends and diagnosing diseases to powering the virtual assistants in our smartphones and enabling self-driving cars, and picking up the slack on your online dating conversations. What makes this book unique is its structure and depth. With 100 chapters, each dedicated to a different machine learning concept, this book is designed to be your ultimate guide to the world of machine learning algorithms. Whether you are a student, a data science professional, or someone curious about machine learning, this book aims to provide a comprehensive overview that is both accessible and in-depth. The algorithms covered in this book span various categories including: Classification & Regression: Learn about algorithms like Decision Trees, Random Forests, Support Vector Machines, and Logistic Regression which are used to classify data or predict numerical values. Clustering: Discover algorithms like k-Means, Hierarchical Clustering, and DBSCAN that group data points together based on similarities. Neural Networks & Deep Learning: Dive into algorithms and architectures like Perceptrons, Convolutional Neural Networks (CNN), and Long Short-Term Memory Networks (LSTM). Optimization: Understand algorithms like Gradient Descent, Genetic Algorithms, and Particle Swarm Optimization which find the best possible solutions in different scenarios. Ensemble Methods: Explore algorithms like AdaBoost, Gradient Boosting, and Random Forests which combine the predictions of multiple models for improved accuracy. Dimensionality Reduction: Learn about algorithms like Principal Component Analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE) which reduce the number of features in a dataset while retaining important information. Reinforcement Learning: Get to know algorithms like Q-learning, Deep Q-Network (DQN), and Monte Carlo Tree Search which are used in systems that learn from their environment. Each chapter is designed as a standalone introduction to its respective algorithm. This means you can start from any chapter that catches your interest or proceed sequentially. Along with the theory, practical examples, applications, and insights into how these algorithms work under the hood are provided. This book is not just an academic endeavor but a bridge that connects theory with practical real-world applications. It's an invitation to explore, learn, and harness the power of algorithms to solve complex problems and make informed decisions. Fasten your seat belts as we dive into the mesmerizing world of machine learning algorithms. Whether you are looking to expand your knowledge, seeking inspiration, or in pursuit of technical mastery, this book should sit on your coffee table and make you look intelligent in front of all invited (and uninvited) guests.



Global Perspectives On Antiviral Drug Development


Global Perspectives On Antiviral Drug Development
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Author : Aslam, Muhammad Shahzad
language : en
Publisher: IGI Global
Release Date : 2025-05-28

Global Perspectives On Antiviral Drug Development written by Aslam, Muhammad Shahzad and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-28 with Medical categories.


The development of antiviral drugs has become a critical part of public health efforts, especially in the context of global viral outbreaks. Nations continue adopting diverse strategies to combat viral infections, shaped by differences in scientific infrastructure, regulatory frameworks, economics, and public health priorities. While high-income countries often lead in drug discovery and clinical trials, lower- and middle-income nations contribute through data and innovative approaches. This global perspective shows the importance of international collaboration and equitable access in the development, testing, and distribution of antiviral therapies. Global Perspectives on Antiviral Drug Development explores the global landscape of antiviral drug development, deployment, and management. It offers an in-depth look at how different countries and regions around the world tackle viral threats, with a strong emphasis on the strategies that shape public health and the innovations driving the future of antiviral treatments. This book covers topics such as vaccines, pharmacology, and personalized medicine, and is a useful resource for medical and healthcare professionals, engineers, academicians, researchers, and scientists.



Bioinformatics With Python Cookbook


Bioinformatics With Python Cookbook
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Author : Tiago Antao
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-09-27

Bioinformatics With Python Cookbook written by Tiago Antao and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-27 with Computers categories.


Discover modern, next-generation sequencing libraries from the powerful Python ecosystem to perform cutting-edge research and analyze large amounts of biological data Key Features Perform complex bioinformatics analysis using the most essential Python libraries and applications Implement next-generation sequencing, metagenomics, automating analysis, population genetics, and much more Explore various statistical and machine learning techniques for bioinformatics data analysis Book Description Bioinformatics is an active research field that uses a range of simple-to-advanced computations to extract valuable information from biological data, and this book will show you how to manage these tasks using Python. This updated third edition of the Bioinformatics with Python Cookbook begins with a quick overview of the various tools and libraries in the Python ecosystem that will help you convert, analyze, and visualize biological datasets. Next, you'll cover key techniques for next-generation sequencing, single-cell analysis, genomics, metagenomics, population genetics, phylogenetics, and proteomics with the help of real-world examples. You'll learn how to work with important pipeline systems, such as Galaxy servers and Snakemake, and understand the various modules in Python for functional and asynchronous programming. This book will also help you explore topics such as SNP discovery using statistical approaches under high-performance computing frameworks, including Dask and Spark. In addition to this, you'll explore the application of machine learning algorithms in bioinformatics. By the end of this bioinformatics Python book, you'll be equipped with the knowledge you need to implement the latest programming techniques and frameworks, empowering you to deal with bioinformatics data on every scale. What you will learn Become well-versed with data processing libraries such as NumPy, pandas, arrow, and zarr in the context of bioinformatic analysis Interact with genomic databases Solve real-world problems in the fields of population genetics, phylogenetics, and proteomics Build bioinformatics pipelines using a Galaxy server and Snakemake Work with functools and itertools for functional programming Perform parallel processing with Dask on biological data Explore principal component analysis (PCA) techniques with scikit-learn Who this book is for This book is for bioinformatics analysts, data scientists, computational biologists, researchers, and Python developers who want to address intermediate-to-advanced biological and bioinformatics problems. Working knowledge of the Python programming language is expected. Basic knowledge of biology will also be helpful.



Sustainable Development Seen Through The Lenses Of Ethnoeconomics And The Circular Economy


Sustainable Development Seen Through The Lenses Of Ethnoeconomics And The Circular Economy
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Author : Walter Leal Filho
language : en
Publisher: Springer Nature
Release Date : 2024-11-22

Sustainable Development Seen Through The Lenses Of Ethnoeconomics And The Circular Economy written by Walter Leal Filho and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-22 with Business & Economics categories.


This book introduces ethnoeconomics, explaining how cultural, social, and historical factors influence economic behavior and decision-making. The book also delves into the principles of the circular economy, emphasizing the importance of designing out waste, keeping products and materials in use, and regenerating natural systems. It explores how these principles can contribute to sustainable economic growth and resilience. The book also explores how insights from ethnoeconomics can inform and enhance the implementation of circular economy principles, with case studies and theoretical frameworks that showcase the benefits of this integration for sustainable development.