Download or read book Microbial Metabolomics written by Edward E.K. Baidoo and published by Humana. This book was released on 2018-11-13 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This detailed volume includes protocols that represent the breadth of microbial metabolomics approaches to both large-scale and small-scale experiments with intention of highlighting techniques that can be used for applications ranging from environmental microbiology to human disease. Utilizing mass spectrometry as their primary measurement tool, the chapters explore microbial metabolomics, metabolism and microbial physiology, metabolite sample preparation, current analytical techniques used to profile primary and secondary metabolites and lipids, as well as establishing data analysis workflows for targeted metabolomics, untargeted metabolomics, analysis of metabolic fluxes, and genome-scale models. Written for the highly successful Methods in Molecular Biology series, chapters include introduction to their respective topics, lists of the necessary materials and reagents, step-by-step readily reproducible protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Microbial Metabolomics: Methods and Protocols serves as an ideal reference for both novice and advanced users and can be adapted to similar analytical platforms or customized to suit the needs of the researcher.

Download or read book Plant Metabolomics written by Kazuki Saito and published by Springer Science & Business Media. This book was released on 2006-06-29 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: Metabolomics – which deals with all metabolites of an organism – is a rapidly-emerging sector of post-genome research fields. It plays significant roles in a variety of fields from medicine to agriculture and holds a fundamental position in functional genomics studies and their application in plant biotechnology. This volume comprehensively covers plant metabolomics for the first time. The chapters offer cutting-edge information on analytical technology, bioinformatics and applications. They were all written by leading researchers who have been directly involved in plant metabolomics research throughout the world. Up-to-date information and future developments are described, thereby producing a volume which is a landmark of plant metabolomics research and a beneficial guideline to graduate students and researchers in academia, industry, and technology transfer organizations in all plant science fields.

Download or read book Processing Metabolomics and Proteomics Data with Open Software written by Robert Winkler and published by Royal Society of Chemistry. This book was released on 2020-03-19 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: Metabolomics and proteomics allow deep insights into the chemistry and physiology of biological systems. This book expounds open-source programs, platforms and programming tools for analysing metabolomics and proteomics mass spectrometry data. In contrast to commercial software, open-source software is created by the academic community, which facilitates the direct interaction between users and developers and accelerates the implementation of new concepts and ideas. The first section of the book covers the basics of mass spectrometry, experimental strategies, data operations, the open-source philosophy, metabolomics, proteomics and statistics/ data mining. In the second section, active programmers and users describe available software packages. Included tutorials, datasets and code examples can be used for training and for building custom workflows. Finally, every reader is invited to participate in the open science movement.

Download or read book Metabolomics Data Processing and Data Analysis Current Best Practices written by Justin Van Der Hooft and published by Mdpi AG. This book was released on 2021-09-10 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Metabolomics data analysis strategies are central to transforming raw metabolomics data files into meaningful biochemical interpretations that answer biological questions or generate novel hypotheses. This book contains a variety of papers from a Special Issue around the theme "Best Practices in Metabolomics Data Analysis". Reviews and strategies for the whole metabolomics pipeline are included, whereas key areas such as metabolite annotation and identification, compound and spectral databases and repositories, and statistical analysis are highlighted in various papers. Altogether, this book contains valuable information for researchers just starting in their metabolomics career as well as those that are more experienced and look for additional knowledge and best practice to complement key parts of their metabolomics workflows.

Download or read book Deep Learning with Azure written by Mathew Salvaris and published by Apress. This book was released on 2018-08-24 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get up-to-speed with Microsoft's AI Platform. Learn to innovate and accelerate with open and powerful tools and services that bring artificial intelligence to every data scientist and developer. Artificial Intelligence (AI) is the new normal. Innovations in deep learning algorithms and hardware are happening at a rapid pace. It is no longer a question of should I build AI into my business, but more about where do I begin and how do I get started with AI? Written by expert data scientists at Microsoft, Deep Learning with the Microsoft AI Platform helps you with the how-to of doing deep learning on Azure and leveraging deep learning to create innovative and intelligent solutions. Benefit from guidance on where to begin your AI adventure, and learn how the cloud provides you with all the tools, infrastructure, and services you need to do AI. What You'll Learn Become familiar with the tools, infrastructure, and services available for deep learning on Microsoft Azure such as Azure Machine Learning services and Batch AI Use pre-built AI capabilities (Computer Vision, OCR, gender, emotion, landmark detection, and more) Understand the common deep learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs) with sample code and understand how the field is evolving Discover the options for training and operationalizing deep learning models on Azure Who This Book Is For Professional data scientists who are interested in learning more about deep learning and how to use the Microsoft AI platform. Some experience with Python is helpful.

Download or read book Computational Biology and Machine Learning for Metabolic Engineering and Synthetic Biology written by Kumar Selvarajoo and published by Springer Nature. This book was released on 2022-10-13 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides protocols for computational, statistical, and machine learning methods that are mainly applied to the study of metabolic engineering, synthetic biology, and disease applications. These techniques support the latest progress in cross-disciplinary research that integrates the different scales of biological complexity. The topics covered in this book are geared toward researchers with a background in engineering, computational analytical, and modeling experience and cover a broad range of topics in computational and machine learning approaches. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Comprehensive and practical, Computational Biology and Machine Learning for Metabolic Engineering and Synthetic Biology is a valuable resource for any researcher or scientist who wants to learn more about the latest computational methods and how they are applied toward the understanding and prediction of complex biology.

Download or read book Learning Deep Architectures for AI written by Yoshua Bengio and published by Now Publishers Inc. This book was released on 2009 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theoretical results suggest that in order to learn the kind of complicated functions that can represent high-level abstractions (e.g. in vision, language, and other AI-level tasks), one may need deep architectures. Deep architectures are composed of multiple levels of non-linear operations, such as in neural nets with many hidden layers or in complicated propositional formulae re-using many sub-formulae. Searching the parameter space of deep architectures is a difficult task, but learning algorithms such as those for Deep Belief Networks have recently been proposed to tackle this problem with notable success, beating the state-of-the-art in certain areas. This paper discusses the motivations and principles regarding learning algorithms for deep architectures, in particular those exploiting as building blocks unsupervised learning of single-layer models such as Restricted Boltzmann Machines, used to construct deeper models such as Deep Belief Networks.

Download or read book Mass Spectrometry for Metabolomics written by Raúl González-Domínguez and published by Springer Nature. This book was released on 2022-09-24 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: This detailed volume provides a comprehensive overview of state-of-the-art metabolomics methods based on mass spectrometry (MS), and their application in food, nutrition, and biomedical research. The chapters assembled herein cover hot topics related to sample preparation, chromatographic and electrophoretic separation, MS-based analysis, as well as data processing and analysis. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step and readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Mass Spectrometry for Metabolomics serves as a timely guide for chemists, biochemists, biologists, nutritionists, clinicians, and other experts working in the growing and exciting field of metabolomics.

Download or read book Comprehensive Foodomics written by and published by Elsevier. This book was released on 2020-11-12 with total page 2444 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive Foodomics, Three Volume Set offers a definitive collection of over 150 articles that provide researchers with innovative answers to crucial questions relating to food quality, safety and its vital and complex links to our health. Topics covered include transcriptomics, proteomics, metabolomics, genomics, green foodomics, epigenetics and noncoding RNA, food safety, food bioactivity and health, food quality and traceability, data treatment and systems biology. Logically structured into 10 focused sections, each article is authored by world leading scientists who cover the whole breadth of Omics and related technologies, including the latest advances and applications. By bringing all this information together in an easily navigable reference, food scientists and nutritionists in both academia and industry will find it the perfect, modern day compendium for frequent reference. List of sections and Section Editors: Genomics - Olivia McAuliffe, Dept of Food Biosciences, Moorepark, Fermoy, Co. Cork, Ireland Epigenetics & Noncoding RNA - Juan Cui, Department of Computer Science & Engineering, University of Nebraska-Lincoln, Lincoln, NE Transcriptomics - Robert Henry, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, Australia Proteomics - Jens Brockmeyer, Institute of Biochemistry and Technical Biochemistry, University Stuttgart, Germany Metabolomics - Philippe Schmitt-Kopplin, Research Unit Analytical BioGeoChemistry, Neuherberg, Germany Omics data treatment, System Biology and Foodomics - Carlos Leon Canseco, Visiting Professor, Biomedical Engineering, Universidad Carlos III de Madrid Green Foodomics - Elena Ibanez, Foodomics Lab, CIAL, CSIC, Madrid, Spain Food safety and Foodomics - Djuro Josic, Professor Medicine (Research) Warren Alpert Medical School, Brown University, Providence, RI, USA & Sandra Kraljevic Pavelic, University of Rijeka, Department of Biotechnology, Rijeka, Croatia Food Quality, Traceability and Foodomics - Daniel Cozzolino, Centre for Nutrition and Food Sciences, The University of Queensland, Queensland, Australia Food Bioactivity, Health and Foodomics - Miguel Herrero, Department of Bioactivity and Food Analysis, Foodomics Lab, CIAL, CSIC, Madrid, Spain Brings all relevant foodomics information together in one place, offering readers a ‘one-stop,’ comprehensive resource for access to a wealth of information Includes articles written by academics and practitioners from various fields and regions Provides an ideal resource for students, researchers and professionals who need to find relevant information quickly and easily Includes content from high quality authors from across the globe

Download or read book Liquid Chromatography Mass Spectrometry MS MS and Time of Flight MS written by Imma Ferrer and published by American Chemical Society. This book was released on 2003-08-14 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume explores state-of-the-art mass spectrometric techniques. It focuses on liquid chromatography/mass spectrometry/mass spectrometry and time-of-flight/mass spectrometry to determine emerging contaminants, such as pharmaceuticals, hormones, pesticides, surfactants and unknown natural products.

Download or read book Concepts and Techniques in OMICS and System Biology written by Asmat Farooq and published by Elsevier. This book was released on 2024-08-23 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Concepts and Techniques in OMICS and Systems Biology provides a concise and lucid account on the technical aspects of omics, system biology and their application in fields of different life science. With a strong focus on the fundamental principles understanding of metabolomics, ionomics and system biology, the book also gives an updated account on technical aspects of omics and system biology. Since both omics and systems biology fields are fast advancing filed of biological sciences, its significance and applications need to be understood from the baseline. In 10 chapters Concepts and Techniques in OMICS and Systems Biology introduces the reader to both Proteomics, Metabolomics and Ionomics, and System Biology, the technical applications, describes both the software in for proteomics as metabolomic enumeration and preludes Omics technologies and their applications. The chapters are designed in a well-defined chronology such that readers will understand the concepts and techniques involved in omics and system biology. This compilation will be ideal reading material for students, researchers and people working in the industries related to biological sciences. Provides an in-depth explanation of fundamental principles regarding the understanding of metabolomics, ionomics and system biology. Gives updated account on technical aspects of omics and system biology. Includes unique content in its theoretical background, technical approaches and advancements made in omics and systems biology

Download or read book Computational Methods and Data Analysis for Metabolomics written by and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Intelligent Computing in Bioinformatics written by De-Shuang Huang and published by Springer. This book was released on 2014-07-03 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book – in conjunction with the volumes LNCS 8588 and LNAI 8589 – constitutes the refereed proceedings of the 10th International Conference on Intelligent Computing, ICIC 2014, held in Taiyuan, China, in August 2014. The 58 papers of this volume were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections such as machine learning; neural networks; image processing; computational systems biology and medical informatics; biomedical informatics theory and methods; advances on bio-inspired computing; protein and gene bioinformatics: analysis, algorithms, applications.

Download or read book Deep Learning with R written by François Chollet and published by Simon and Schuster. This book was released on 2018-01-22 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Deep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through intuitive explanations and practical examples. Continue your journey into the world of deep learning with Deep Learning with R in Motion, a practical, hands-on video course available exclusively at Manning.com (www.manning.com/livevideo/deep-​learning-with-r-in-motion). Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. Deep-learning systems now enable previously impossible smart applications, revolutionizing image recognition and natural-language processing, and identifying complex patterns in data. The Keras deep-learning library provides data scientists and developers working in R a state-of-the-art toolset for tackling deep-learning tasks. About the Book Deep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface. Initially written for Python as Deep Learning with Python by Keras creator and Google AI researcher François Chollet and adapted for R by RStudio founder J. J. Allaire, this book builds your understanding of deep learning through intuitive explanations and practical examples. You'll practice your new skills with R-based applications in computer vision, natural-language processing, and generative models. What's Inside Deep learning from first principles Setting up your own deep-learning environment Image classification and generation Deep learning for text and sequences About the Reader You'll need intermediate R programming skills. No previous experience with machine learning or deep learning is assumed. About the Authors François Chollet is a deep-learning researcher at Google and the author of the Keras library. J.J. Allaire is the founder of RStudio and the author of the R interfaces to TensorFlow and Keras. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions

Download or read book Medical Image Computing and Computer Assisted Intervention MICCAI 2015 written by Nassir Navab and published by Springer. This book was released on 2015-09-28 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 9349, 9350, and 9351 constitutes the refereed proceedings of the 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015, held in Munich, Germany, in October 2015. Based on rigorous peer reviews, the program committee carefully selected 263 revised papers from 810 submissions for presentation in three volumes. The papers have been organized in the following topical sections: quantitative image analysis I: segmentation and measurement; computer-aided diagnosis: machine learning; computer-aided diagnosis: automation; quantitative image analysis II: classification, detection, features, and morphology; advanced MRI: diffusion, fMRI, DCE; quantitative image analysis III: motion, deformation, development and degeneration; quantitative image analysis IV: microscopy, fluorescence and histological imagery; registration: method and advanced applications; reconstruction, image formation, advanced acquisition - computational imaging; modelling and simulation for diagnosis and interventional planning; computer-assisted and image-guided interventions.

Download or read book MATLAB Deep Learning written by Phil Kim and published by Apress. This book was released on 2017-06-15 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, MATLAB Deep Learning employs MATLAB as the underlying programming language and tool for the examples and case studies in this book. With this book, you'll be able to tackle some of today's real world big data, smart bots, and other complex data problems. You’ll see how deep learning is a complex and more intelligent aspect of machine learning for modern smart data analysis and usage. What You'll Learn Use MATLAB for deep learning Discover neural networks and multi-layer neural networks Work with convolution and pooling layers Build a MNIST example with these layers Who This Book Is For Those who want to learn deep learning using MATLAB. Some MATLAB experience may be useful.

Download or read book Integrative Omics written by Manish Kumar Gupta and published by Elsevier. This book was released on 2024-05-03 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrative Omics: Concepts, Methodology and Applications provides a holistic and integrated view of defining and applying network approaches, integrative tools, and methods to solve problems for the rationalization of genotype to phenotype relationships. The reference includes a range of chapters in a systemic 'step by step' manner, which begins with the basic concepts from Omic to Multi Integrative Omics approaches, followed by their full range of approaches, applications, emerging trends, and future trends. All key areas of Omics are covered including biological databases, sequence alignment, pharmacogenomics, nutrigenomics and microbial omics, integrated omics for Food Science and Identification of genes associated with disease, clinical data integration and data warehousing, translational omics as well as omics technology policy and society research. Integrative Omics: Concepts, Methodology and Applications highlights the recent concepts, methodologies, advancements in technologies and is also well-suited for researchers from both academic and industry background, undergraduate and graduate students who are mainly working in the area of computational systems biology, integrative omics and translational science. The book bridges the gap between biological sciences, physical sciences, computer science, statistics, data science, information technology and mathematics by presenting content specifically dedicated to mathematical models of biological systems. - Provides a holistic, integrated view of a defining and applying network approach, integrative tools, and methods to solve problems for rationalization of genotype to phenotype relationships - Offers an interdisciplinary approach to Databases, data analytics techniques, biological tools, network construction, analysis, modeling, prediction and simulation of biological systems leading to 'translational research', i.e., drug discovery, drug target prediction, and precision medicine - Covers worldwide methods, concepts, databases, and tools used in the construction of integrated pathways