Bioinformatics for Omics Data

Bioinformatics for Omics Data

Author: Bernd Mayer

Publisher: Springer Science+Business Media

Published: 2011-01-01

Total Pages: 584

ISBN-13: 9781617790270

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Presenting an area of research that intersects with and integrates diverse disciplines, Bioinformatics for Omics Data: Methods and Protocols collects contributions from expert researchers in order to provide practical guidelines to this complex study.


Bioinformatics for Omics Data

Bioinformatics for Omics Data

Author: Bernd Mayer

Publisher: Humana Press

Published: 2011-03-03

Total Pages: 0

ISBN-13: 9781617790263

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Presenting an area of research that intersects with and integrates diverse disciplines, including molecular biology, applied informatics, and statistics, among others, Bioinformatics for Omics Data: Methods and Protocols collects contributions from expert researchers in order to provide practical guidelines to this complex study. Divided into three convenient sections, this detailed volume covers central analysis strategies, standardization and data-management guidelines, and fundamental statistics for analyzing Omics profiles, followed by a section on bioinformatics approaches for specific Omics tracks, spanning genome, transcriptome, proteome, and metabolome levels, as well as an assortment of examples of integrated Omics bioinformatics applications, complemented by case studies on biomarker and target identification in the context of human disease. Written in the highly successful Methods in Molecular BiologyTM series format, chapters contain introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and notes on troubleshooting and avoiding known pitfalls. Authoritative and accessible, Bioinformatics for Omics Data: Methods and Protocols serves as an ideal guide to scientists of all backgrounds and aims to convey the appropriate sense of fascination associated with this research field.


Evolution of Translational Omics

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.


Artificial Intelligence in Bioinformatics

Artificial Intelligence in Bioinformatics

Author: Mario Cannataro

Publisher: Elsevier

Published: 2022-05-12

Total Pages: 270

ISBN-13: 0128229292

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Artificial Intelligence in Bioinformatics: From Omics Analysis to Deep Learning and Network Mining reviews the main applications of the topic, from omics analysis to deep learning and network mining. The book includes a rigorous introduction on bioinformatics, also reviewing how methods are incorporated in tasks and processes. In addition, it presents methods and theory, including content for emergent fields such as Sentiment Analysis and Network Alignment. Other sections survey how Artificial Intelligence is exploited in bioinformatics applications, including sequence analysis, structure analysis, functional analysis, protein classification, omics analysis, biomarker discovery, integrative bioinformatics, protein interaction analysis, metabolic networks analysis, and much more. - Bridges the gap between computer science and bioinformatics, combining an introduction to Artificial Intelligence methods with a systematic review of its applications in the life sciences - Brings readers up-to-speed on current trends and methods in a dynamic and growing field - Provides academic teachers with a complete resource, covering fundamental concepts as well as applications


Molecular Pathology of Lung Diseases

Molecular Pathology of Lung Diseases

Author: Dani S. Zander

Publisher: Springer Science & Business Media

Published: 2010-05-26

Total Pages: 691

ISBN-13: 0387724303

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This major work, complete with 150 illustrations, many of them in color, bridges the gap between clinical pulmonary pathology and basic molecular science. Through a highly visual approach that features an abundance of tables and diagrams, the book offers a practical disease-based overview. The first two sections of the volume provide the reader with general concepts, terminology and procedures in molecular pathology. The remainder of the volume is subdivided into neoplastic and non-neoplastic lung diseases with detailed chapters covering the current molecular pathology of specific diseases. The book will be essential reading for pathologists, pulmonologists, thoracic surgeons and other health care providers interested in lung disease.


Application Of Omics, Ai And Blockchain In Bioinformatics Research

Application Of Omics, Ai And Blockchain In Bioinformatics Research

Author: Jeffrey J P Tsai

Publisher: World Scientific

Published: 2019-10-14

Total Pages: 207

ISBN-13: 9811203598

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With the increasing availability of omics data and mounting evidence of the usefulness of computational approaches to tackle multi-level data problems in bioinformatics and biomedical research in this post-genomics era, computational biology has been playing an increasingly important role in paving the way as basis for patient-centric healthcare.Two such areas are: (i) implementing AI algorithms supported by biomedical data would deliver significant benefits/improvements towards the goals of precision medicine (ii) blockchain technology will enable medical doctors to securely and privately build personal healthcare records, and identify the right therapeutic treatments and predict the progression of the diseases.A follow-up in the publication of our book Computation Methods with Applications in Bioinformatics Analysis (2017), topics in this volume include: clinical bioinformatics, omics-based data analysis, Artificial Intelligence (AI), blockchain, big data analytics, drug discovery, RNA-seq analysis, tensor decomposition and Boolean network.


Integrating Omics Data

Integrating Omics Data

Author: George Tseng

Publisher: Cambridge University Press

Published: 2015-09-23

Total Pages: 497

ISBN-13: 1107069114

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Tutorial chapters by leaders in the field introduce state-of-the-art methods to handle information integration problems of omics data.


Data Analytics in Bioinformatics

Data Analytics in Bioinformatics

Author: Rabinarayan Satpathy

Publisher: John Wiley & Sons

Published: 2021-01-20

Total Pages: 433

ISBN-13: 111978560X

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Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning 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. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.


Encyclopedia of Bioinformatics and Computational Biology

Encyclopedia of Bioinformatics and Computational Biology

Author:

Publisher: Elsevier

Published: 2018-08-21

Total Pages: 3421

ISBN-13: 0128114320

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Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics, Three Volume Set combines elements of computer science, information technology, mathematics, statistics and biotechnology, providing the methodology and in silico solutions to mine biological data and processes. The book covers Theory, Topics and Applications, with a special focus on Integrative –omics and Systems Biology. The theoretical, methodological underpinnings of BCB, including phylogeny are covered, as are more current areas of focus, such as translational bioinformatics, cheminformatics, and environmental informatics. Finally, Applications provide guidance for commonly asked questions. This major reference work spans basic and cutting-edge methodologies authored by leaders in the field, providing an invaluable resource for students, scientists, professionals in research institutes, and a broad swath of researchers in biotechnology and the biomedical and pharmaceutical industries. Brings together information from computer science, information technology, mathematics, statistics and biotechnology Written and reviewed by leading experts in the field, providing a unique and authoritative resource Focuses on the main theoretical and methodological concepts before expanding on specific topics and applications Includes interactive images, multimedia tools and crosslinking to further resources and databases


Omic Association Studies with R and Bioconductor

Omic Association Studies with R and Bioconductor

Author: Juan R. González

Publisher: CRC Press

Published: 2019-06-14

Total Pages: 356

ISBN-13: 0429803362

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After the great expansion of genome-wide association studies, their scientific methodology and, notably, their data analysis has matured in recent years, and they are a keystone in large epidemiological studies. Newcomers to the field are confronted with a wealth of data, resources and methods. This book presents current methods to perform informative analyses using real and illustrative data with established bioinformatics tools and guides the reader through the use of publicly available data. Includes clear, readable programming codes for readers to reproduce and adapt to their own data. Emphasises extracting biologically meaningful associations between traits of interest and genomic, transcriptomic and epigenomic data Uses up-to-date methods to exploit omic data Presents methods through specific examples and computing sessions Supplemented by a website, including code, datasets, and solutions