Name: Multivariate Biomarker Discovery: Data Science Methods for Efficient Analysis of High-Dimensional Biomedical Data (en Inglés)
SKU: 57313836
Price: 106.59 USD
Availability: InStock
Author: Dziuda, Darius M.
ISBN: 9781316518700

portada Multivariate Biomarker Discovery: Data Science Methods for Efficient Analysis of High-Dimensional Biomedical Data (en Inglés)

Multivariate Biomarker Discovery: Data Science Methods for Efficient Analysis of High-Dimensional Biomedical Data (en Inglés)

Formato

Libro Físico

Autor

Darius M. Dziuda

Editorial

Cambridge University Press

Idioma

Inglés

N° páginas

300

Encuadernación

Tapa Dura

ISBN13

9781316518700

Categorías

Investigación médica
Genética (no médica)

Multivariate Biomarker Discovery: Data Science Methods for Efficient Analysis of High-Dimensional Biomedical Data (en Inglés)

Darius M. Dziuda (Autor) · Cambridge University Press · Tapa Dura

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Reseña del libro "Multivariate Biomarker Discovery: Data Science Methods for Efficient Analysis of High-Dimensional Biomedical Data (en Inglés)"

Multivariate biomarker discovery is increasingly important in the realm of biomedical research, and is poised to become a crucial facet of personalized medicine. This will prompt the demand for a myriad of novel biomarkers representing distinct 'omic' biosignatures, allowing selection and tailoring treatments to the various individual characteristics of a particular patient. This concise and self-contained book covers all aspects of predictive modeling for biomarker discovery based on high-dimensional data, as well as modern data science methods for identification of parsimonious and robust multivariate biomarkers for medical diagnosis, prognosis, and personalized medicine. It provides a detailed description of state-of-the-art methods for parallel multivariate feature selection and supervised learning algorithms for regression and classification, as well as methods for proper validation of multivariate biomarkers and predictive models implementing them. This is an invaluable resource for scientists and students interested in bioinformatics, data science, and related areas.