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Data Analysis for Omic Sciences: Methods and Applications

Author:

Publisher: Elsevier

Published: 2018-09-22

Total Pages: 730

ISBN-13: 0444640452

Data Analysis for Omic Sciences: Methods and Applications, Volume 82, shows how these types of challenging datasets can be analyzed. Examples of applications in real environmental, clinical and food analysis cases help readers disseminate these approaches. Chapters of note include an Introduction to Data Analysis Relevance in the Omics Era, Omics Experimental Design and Data Acquisition, Microarrays Data, Analysis of High-Throughput RNA Sequencing Data, Analysis of High-Throughput DNA Bisulfite Sequencing Data, Data Quality Assessment in Untargeted LC-MS Metabolomic, Data Normalization and Scaling, Metabolomics Data Preprocessing, and more. Presents the best reference book for omics data analysis Provides a review of the latest trends in transcriptomics and metabolomics data analysis tools Includes examples of applications in research fields, such as environmental, biomedical and food analysis

Multi-omic Data Integration

Author: Paolo Tieri

Publisher: Frontiers Media SA

Published: 2015-09-17

Total Pages: 137

ISBN-13: 2889196488

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Stable, predictive biomarkers and interpretable disease signatures are seen as a significant step towards personalized medicine. In this perspective, integration of multi-omic data coming from genomics, transcriptomics, glycomics, proteomics, metabolomics is a powerful strategy to reconstruct and analyse complex multi-dimensional interactions, enabling deeper mechanistic and medical insight. At the same time, there is a rising concern that much of such different omic data –although often publicly and freely available- lie in databases and repositories underutilised or not used at all. Issues coming from lack of standardisation and shared biological identities are also well-known. From these considerations, a novel, pressing request arises from the life sciences to design methodologies and approaches that allow for these data to be interpreted as a whole, i.e. as intertwined molecular signatures containing genes, proteins, mRNAs and miRNAs, able to capture inter-layers connections and complexity. Papers discuss data integration approaches and methods of several types and extents, their application in understanding the pathogenesis of specific diseases or in identifying candidate biomarkers to exploit the full benefit of multi-omic datasets and their intrinsic information content. Topics of interest include, but are not limited to: • Methods for the integration of layered data, including, but not limited to, genomics, transcriptomics, glycomics, proteomics, metabolomics; • Application of multi-omic data integration approaches for diagnostic biomarker discovery in any field of the life sciences; • Innovative approaches for the analysis and the visualization of multi-omic datasets; • Methods and applications for systematic measurements from single/undivided samples (comprising genomic, transcriptomic, proteomic, metabolomic measurements, among others); • Multi-scale approaches for integrated dynamic modelling and simulation; • Implementation of applications, computational resources and repositories devoted to data integration including, but not limited to, data warehousing, database federation, semantic integration, service-oriented and/or wiki integration; • Issues related to the definition and implementation of standards, shared identities and semantics, with particular focus on the integration problem. Research papers, reviews and short communications on all topics related to the above issues were welcomed.

Bioinformatics and Biomarker Discovery

Author: Francisco Azuaje

Publisher: John Wiley & Sons

Published: 2011-08-24

Total Pages: 206

ISBN-13: 111996430X

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This book is designed to introduce biologists, clinicians and computational researchers to fundamental data analysis principles, techniques and tools for supporting the discovery of biomarkers and the implementation of diagnostic/prognostic systems. The focus of the book is on how fundamental statistical and data mining approaches can support biomarker discovery and evaluation, emphasising applications based on different types of "omic" data. The book also discusses design factors, requirements and techniques for disease screening, diagnostic and prognostic applications. Readers are provided with the knowledge needed to assess the requirements, computational approaches and outputs in disease biomarker research. Commentaries from guest experts are also included, containing detailed discussions of methodologies and applications based on specific types of "omic" data, as well as their integration. Covers the main range of data sources currently used for biomarker discovery Covers the main range of data sources currently used for biomarker discovery Puts emphasis on concepts, design principles and methodologies that can be extended or tailored to more specific applications Offers principles and methods for assessing the bioinformatic/biostatistic limitations, strengths and challenges in biomarker discovery studies Discusses systems biology approaches and applications Includes expert chapter commentaries to further discuss relevance of techniques, summarize biological/clinical implications and provide alternative interpretations

Evolution of Translational Omics

Author: Institute of Medicine

Publisher: National Academies Press

Published: 2012-09-13

Total Pages: 354

ISBN-13: 0309224187

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Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.

Biomedical Applications of Microfluidic Devices

Author: Michael R. Hamblin

Publisher: Academic Press

Published: 2020-11-12

Total Pages: 352

ISBN-13: 0128187921

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Biomedical Applications of Microfluidic Devices introduces the subject of microfluidics and covers the basic principles of design and synthesis of actual microchannels. The book then explores how the devices are coupled to signal read-outs and calibrated, including applications of microfluidics in areas such as tissue engineering, organ-on-a-chip devices, pathogen identification, and drug/gene delivery. This book covers high-impact fields (microarrays, organ-on-a-chip, pathogen detection, cancer research, drug delivery systems, gene delivery, and tissue engineering) and shows how microfluidics is playing a key role in these areas, which are big drivers in biomedical engineering research. This book addresses the fundamental concepts and fabrication methods of microfluidic systems for those who want to start working in the area or who want to learn about the latest advances being made. The subjects covered are also an asset to companies working in this field that need to understand the current state-of-the-art. The book is ideal for courses on microfluidics, biosensors, drug targeting, and BioMEMs, and as a reference for PhD students. The book covers the emerging and most promising areas of biomedical applications of microfluidic devices in a single place and offers a vision of the future. Covers basic principles and design of microfluidics devices Explores biomedical applications to areas such as tissue engineering, organ-on-a-chip, pathogen identification, and drug and gene delivery Includes chemical applications in organic and inorganic chemistry Serves as an ideal text for courses on microfluidics, biosensors, drug targeting, and BioMEMs, as well as a reference for PhD students

Data Analysis and Chemometrics for Metabolomics

Author: Richard G. Brereton

Publisher: John Wiley & Sons

Published: 2024-07-08

Total Pages: 437

ISBN-13: 1119639409

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Understand new modes of analysing metabolomic data Metabolomics is the study of metabolites, small molecules and chemical substrates within cells or larger structures which collectively make up the metabolome. The field of metabolomics stands to benefit enormously from chemometrics, an approach which brings advanced statistical techniques to bear on data of this kind. Data Analysis and Chemometrics for Metabolomics constitutes an accessible introduction to chemometric techniques and their applications in the field of metabolomics. Thoroughly and accessibly written by a leading expert in chemometrics, and printed in full-colour, it brings robust data analysis into conversation with the metabolomic field to the immense benefit of practitioners. Data Analysis and Chemometrics for Metabolomics readers will also find: Statistical insights into the nature of metabolomic hypothesis testing, validation, and more All metabolomics data sets from the book on a companion website Case studies from human, animal, plant and bacterial biology Data Analysis and Chemometrics for Metabolomics is ideal for practitioners in the life sciences, clinical sciences and chemistry, as well as metabolomics researchers or developers of research instruments looking to apply cutting-edge analytical techniques, and statisticians developing methods to design experiments and analyse large datasets of clinical and biological origin.

Comprehensive Foodomics

Author:

Publisher: Elsevier

Published: 2020-11-12

Total Pages: 2444

ISBN-13: 0128163968

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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

Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry

Author: Susmita Datta

Publisher: Springer

Published: 2016-12-15

Total Pages: 295

ISBN-13: 3319458094

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This book presents an overview of computational and statistical design and analysis of mass spectrometry-based proteomics, metabolomics, and lipidomics data. This contributed volume provides an introduction to the special aspects of statistical design and analysis with mass spectrometry data for the new omic sciences. The text discusses common aspects of design and analysis between and across all (or most) forms of mass spectrometry, while also providing special examples of application with the most common forms of mass spectrometry. Also covered are applications of computational mass spectrometry not only in clinical study but also in the interpretation of omics data in plant biology studies. Omics research fields are expected to revolutionize biomolecular research by the ability to simultaneously profile many compounds within either patient blood, urine, tissue, or other biological samples. Mass spectrometry is one of the key analytical techniques used in these new omic sciences. Liquid chromatography mass spectrometry, time-of-flight data, and Fourier transform mass spectrometry are but a selection of the measurement platforms available to the modern analyst. Thus in practical proteomics or metabolomics, researchers will not only be confronted with new high dimensional data types—as opposed to the familiar data structures in more classical genomics—but also with great variation between distinct types of mass spectral measurements derived from different platforms, which may complicate analyses, comparison, and interpretation of results.

Metabolomics in Health and Disease Biology

Author:

Publisher: Elsevier

Published: 2024-02-26

Total Pages: 248

ISBN-13: 0443137269

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Metabolomics in Health and Disease Biology, Volume 104 covers this rapidly emerging field that aims for metabolic phenotyping and understanding the blueprint of metabolic pathways under various health and disease conditions by comprehensive analysis of metabolites. Chapters in this new release include Metabolomics approaches: Biomarkers to Disease mechanisms, Metabolomics in sleep disorders, Metabolomics in predicting the hallmark of Cancer Metabolism, Spectroscopic based rapid metabolic fingerprinting approaches for Cancer diagnosis, Lipidomics in assessing the health of osteoarthritis, Metabolomics Applications in Type 2 Diabetes mellitus, Metabolomics of Diabetic retinopathy, Metabolomics in Neurodegenerative disorders- Parkinson's disease, and Metabolomic of Neurodegenerative disorder: Alzheimer's Disease. Presents crucial reviews from selected experts in the field of metabolomics, with cross-disciplinary contributions Provides the latest insights into our understanding of diseases using metabolomics-based approaches Includes graphical material for metabolomics application that provide useful information for ease of reading of audience

Data Analysis and Visualization in Genomics and Proteomics

Author: Francisco Azuaje

Publisher: John Wiley & Sons

Published: 2005-06-24

Total Pages: 284

ISBN-13: 0470094400

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Data Analysis and Visualization in Genomics and Proteomics is the first book addressing integrative data analysis and visualization in this field. It addresses important techniques for the interpretation of data originating from multiple sources, encoded in different formats or protocols, and processed by multiple systems. One of the first systematic overviews of the problem of biological data integration using computational approaches This book provides scientists and students with the basis for the development and application of integrative computational methods to analyse biological data on a systemic scale Places emphasis on the processing of multiple data and knowledge resources, and the combination of different models and systems