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Saturday, November 7, 2020 | History

3 edition of Bioinformatics and biomarker discovery found in the catalog.

Bioinformatics and biomarker discovery

"omic" data analysis for personalised medicine

by Francisco Azuaje

  • 260 Want to read
  • 18 Currently reading

Published by John Wiley & Sons in Hoboken, NJ .
Written in English

    Subjects:
  • Biochemical markers,
  • Bioinformatics,
  • Computational Biology,
  • Biological Markers,
  • Genomics -- methods,
  • Statistics as Topic

  • Edition Notes

    Includes bibliographical references and index.

    StatementFrancisco Azuaje.
    Classifications
    LC ClassificationsR853.B54 A98 2010
    The Physical Object
    Paginationp. ;
    ID Numbers
    Open LibraryOL24053138M
    ISBN 109780470744604
    LC Control Number2009027776


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Bioinformatics and biomarker discovery by Francisco Azuaje Download PDF EPUB FB2

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. ‎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. 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 : $ Bioinformatics and Biomarker Discovery: “Omic” Data Analysis for Personalized Medicine 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. 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 - Selection from Bioinformatics and Biomarker Discovery: "Omic" Data Analysis for Personalized Medicine [Book].

3 Biomarker-based prediction models: design and interpretation principles This chapter will introduce key techniques and applications for patient classification and disease prediction based on multivariate data analysis and machine learning - Selection from Bioinformatics and Biomarker Discovery: "Omic" Data Analysis for Personalized Medicine [Book].

Bioinformatics and biomarker discovery: Omic data analysis for personalized medicine Francisco Azuaje 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.

Keywords:Bioinformatics, biomarker discovery, drug design, drug development, proteomics. Abstract: Novel biomarker identification and drug target validation are highly complex and resource-intensive processes, requiring an integral use of various tools, approaches and information.

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By using our website, you are agreeing to the use of Cookies. You can change your settings at any time. Introduction. Biological markers, also known as markers or biomarkers, are objectively measurable and evaluable indicators of certain biological states in normal and pathogenic processes, or possible pharmacologic responses to therapeutics [1, 2].From a medical point of view, biomarkers are traceable substances with the ability to classify binary conditions (e.g.

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Bioinformatics and Biomarker Discovery: "Omic" Data Analysis for Personalized Medicine 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 Author: Francisco Azuaje. Offers new chapters on biomarker discovery, global phosphorylation analysis, proteomic profiling using antibodies, and single cell mass spectrometry Proteomics for Biological Discovery is an excellent advanced resource for graduate students, postdoctoral fellows, and scientists across all the major fields of biomedical science.

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. Proteomics for Biomarker Discovery: Methods and Protocols Virginie Brun, Yohann Couté This volume presents modern and enhanced methods that detail techniques to perform proteomics analyses dedicated to biomarker discovery for human health.

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, Author: Francisco Azuaje.

[PDF] Bioinformatics and Biomarker Discovery: "Omic" Data Analysis for Personalized Medicine Full. ISBN: X: OCLC Number: Description: xviii, pages: illustrations ; 26 cm: Contents: Biomarkers and bioinformatics --Review of fundamental statistical concepts --Biomarker-based prediction models: design and interpretation principles --An introduction to the discovery and analysis of genotype-phenotype associations --Integrative approaches to genotype.

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The book introduces the bioinformatics tools, databases and strategies for the translational research, focuses on the biomarker discovery based on integrative data analysis and. The book discusses topics such as the challenges and tasks in translational bioinformatics; pharmacogenomics, systems biology, and personalized medicine; and the applicability of translational bioinformatics for biomarker discovery, epigenomics, and molecular dynamics.

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It also discusses data integration and mining, immunoinformatics, and. Mass spectrometry-based proteomics is a continuously growing field marked by technological and methodological improvements. Cancer proteomics is aimed at pursuing goals such as accurate diagnosis, patient stratification, and biomarker discovery, relying on the richness of information of quantitative proteome profiles.

The book covers the protein interaction network, drug discovery and development, the relationship between translational medicine and bioinformatics, and advances in proteomic methods, while also demonstrating important bioinformatics tools and methods available today for protein analysis, interpretation and predication.

In the upcoming articles on Chemometrics in Metabolomics, I will be discussing the raw data analyses part using bioinformatics tools and techniques and also about the statistical investigation for biomarker discovery. Bibliography and Further Reading: Johnson, C.H., Ivanisevic, J., Benton, H.P., Siuzdak, G.,   The progression of biomarker discovery is impossible without bioinformatics, which connects individual discovery processes, including experimental design, study execution, and bioanalytic analysis.

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