Téléchargez le livre : Machine Learning in Single-Cell RNA-seq Data Analysis

Machine Learning in Single-Cell RNA-seq Data Analysis

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Springer


Paru le : 2024-09-02

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Description

This book provides a concise guide tailored for researchers, bioinformaticians, and enthusiasts eager to unravel the mysteries hidden within single-cell RNA sequencing (scRNA-seq) data using cutting-edge machine learning techniques. The advent of scRNA-seq technology has revolutionized our understanding of cellular diversity and function, offering unprecedented insights into the intricate tapestry of gene expression at the single-cell level. However, the deluge of data generated by these experiments presents a formidable challenge, demanding advanced analytical tools, methodologies, and skills for meaningful interpretation. This book bridges the gap between traditional bioinformatics and the evolving landscape of machine learning. Authored by seasoned experts at the intersection of genomics and artificial intelligence, this book serves as a roadmap for leveraging machine learning algorithms to extract meaningful patterns and uncover hidden biological insights within scRNA-seq datasets. 
Pages
88 pages
Collection
n.c
Parution
2024-09-02
Marque
Springer
EAN papier
9789819767021
EAN PDF
9789819767038
Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
8
Taille du fichier
5560 Ko
Prix
52,74 €
EAN EPUB
9789819767038
Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
8
Taille du fichier
10312 Ko
Prix
52,74 €

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