Bioinformatics and Biomarker Discovery

Bioinformatics and Biomarker Discovery PDF

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

Biomedical Image or Genomic Data Characterization and Radiogenomic/Image-omics

Biomedical Image or Genomic Data Characterization and Radiogenomic/Image-omics PDF

Author: Ming Fan

Publisher: Frontiers Media SA

Published: 2022-09-27

Total Pages: 183

ISBN-13: 2832500935

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Much of the emphasis in discussions about personalized medicine has been focused on the molecular characterization of tissue samples using microarray technology. However, as genetic differ between and within tumors and are quite heterogeneous, these techniques are limited. Imaging is noninvasive and is often used in routine clinical practice for disease diagnosis, treatment, and prognosis. Imaging is useful to guide disease therapy by providing a more comprehensive view of the entire lesion and it can be used on an ongoing basis to monitor lesion growth and progression or its response to treatment. The imaging includes but not limited to ultrasound, X-ray, computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET). Radiomics refers to the conversion of images to high dimensional data and the subsequent mining for characterization of biology and ultimately to improve disease management for patients. Radiogenomics investigates relationships between imaging features and genomics, which represents the correlation between the anatomical-histological level to the genomic level. With advanced artificial intelligence methods, especially deep learning, data processing, feature extraction and data integration have been greatly improved. The topic is about artificial intelligence methods in biomedical images and genomics data for disease diagnosis, treatment, and prognosis, as listed here: • Biomarker identification from biomedical images to predict disease diagnosis, treatment, and prognosis • Radiogenomics/image-omics in identifying imaging biomarkers associated with molecular characteristics of the disease. • Machine learning/deep learning methods in biomedical imaging or genomics for disease detection and precision medicine. • Prediction of histological characteristics of disease based on biomedical imaging. • Integration of radiomics and genomics features for disease diagnosis, prognosis, and prediction medicine • Multimodality images or multi-omics data integration methods

Imaging Biomarkers

Imaging Biomarkers PDF

Author: Luis Martí-Bonmatí

Publisher: Springer

Published: 2016-11-03

Total Pages: 313

ISBN-13: 3319435043

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This is the first book to cover all aspects of the development of imaging biomarkers and their integration into clinical practice, from the conceptual basis through to the technical aspects that need to be considered in order to ensure that medical imaging can serve as a powerful quantification instrument capable of providing valuable information on organ and tissue properties. The process of imaging biomarker development is considered step by step, covering proof of concept, proof of mechanism, image acquisition, image preparation, imaging biomarker analysis and measurement, detection of measurement biases (proof of principle), proof of efficacy and effectiveness, and reporting of results. Sources of uncertainty in the accuracy and precision of measurements and pearls and pitfalls in gold standards and biological correlation are discussed. In addition, practical use cases are included on imaging biomarker implementation in brain, oncologic, cardiovascular, musculoskeletal, and abdominal diseases. The authors are a multidisciplinary team of expert radiologists and engineers, and the book will be of value to all with an interest in the quantitative imaging of biomarkers in personalized medicine.

Evolution of Translational Omics

Evolution of Translational Omics PDF

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.

The Detection of Biomarkers

The Detection of Biomarkers PDF

Author: Sibel A. Ozkan

Publisher: Academic Press

Published: 2021-12-05

Total Pages: 615

ISBN-13: 0128230754

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Reliable, precise and accurate detection and analysis of biomarkers remains a significant challenge for clinical researchers. Methods for the detection of biomarkers are rather complex, requiring pre-treatment steps before analysis can take place. Moreover, comparing various biomarker assays and tracing research progress in this area systematically is a challenge for researchers. The Detection of Biomarkers presents developments in biomarker detection, including methods tools and strategies, biosensor design, materials, and applications. The book presents methods, materials and procedures that are simple, precise, sensitive, selective, fast and economical, and therefore highly practical for use in clinical research scenarios. This volume situates biomarker detection in its research context and sets out future prospects for the area. Its 20 chapters offer a comprehensive coverage of biomarkers, including progress on nanotechnology, biosensor types, synthesis, immobilization, and applications in various fields. The book also demonstrates, for students, how to synthesize and immobilize biosensors for biomarker assay. It offers researchers real alternative and innovative ways to think about the field of biomarker detection, increasing the reliability, precision and accuracy of biomarker detection. Locates biomarker detection in its research context, setting out present and future prospects Allows clinical researchers to compare various biomarker assays systematically Presents new methods, materials and procedures that are simple, precise, sensitive, selective, fast and economical Gives innovative biomarker assays that are viable alternatives to current complex methods Helps clinical researchers who need reliable, precise and accurate biomarker detection methods

Biomarker Validation

Biomarker Validation PDF

Author: Harald Seitz

Publisher: John Wiley & Sons

Published: 2015-02-23

Total Pages: 264

ISBN-13: 3527680667

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Built on a decade of experience with novel molecular diagnostics, this practice-oriented guide shows how to cope with validation issues during all stages of biomarker development, from the first clinical studies to the eventual commercialization of a new diagnostic test.

Bioinformatics Analysis of Omics Data for Biomarker Identification in Clinical Research, Volume II

Bioinformatics Analysis of Omics Data for Biomarker Identification in Clinical Research, Volume II PDF

Author: Lixin Cheng

Publisher: Frontiers Media SA

Published: 2023-09-05

Total Pages: 757

ISBN-13: 283253175X

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This Research Topic is part of a series with, "Bioinformatics Analysis of Omics Data for Biomarker Identification in Clinical Research - Volume I" (https://www.frontiersin.org/research-topics/13816/bioinformatics-analysis-of-omics-data-for-biomarker-identification-in-clinical-research) The advances and the decreasing cost of omics data enable profiling of disease molecular features at different levels, including bulk tissues, animal models, and single cells. Large volumes of omics data enhance the ability to search for information for preclinical study and provide the opportunity to leverage them to understand disease mechanisms, identify molecular targets for therapy, and detect biomarkers of treatment response. Identification of stable, predictive, and interpretable biomarkers is a significant step towards personalized medicine and therapy. Omics data from genomics, transcriptomics, proteomics, epigenomics, metagenomics, and metabolomics help to determine biomarkers for prognostic and diagnostic applications. Preprocessing of omics data is of vital importance as it aims to eliminate systematic experimental bias and technical variation while preserving biological variation. Dozens of normalization methods for correcting experimental variation and bias in omics data have been developed during the last two decades, while only a few consider the skewness between different sample states, such as the extensive over-repression of genes in cancers. The choice of normalization methods determines the fate of identified biomarkers or molecular signatures. From these considerations, the development of appropriate normalization methods or preprocessing strategies may promote biomarker identification and facilitate clinical decision-making.

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