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Titlebook: Machine Learning in Single-Cell RNA-seq Data Analysis; Khalid Raza Book 2024 The Editor(s) (if applicable) and The Author(s), under exclus

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发表于 2025-3-21 16:46:43 | 显示全部楼层 |阅读模式
书目名称Machine Learning in Single-Cell RNA-seq Data Analysis
编辑Khalid Raza
视频video
概述Covers basic concepts of single cell RNA-seq.Discusses integration of ML and scRNA-seq.Presents hands-on examples and case studies
丛书名称SpringerBriefs in Applied Sciences and Technology
图书封面Titlebook: Machine Learning in Single-Cell RNA-seq Data Analysis;  Khalid Raza Book 2024 The Editor(s) (if applicable) and The Author(s), under exclus
描述.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. .
出版日期Book 2024
关键词Single Cell Data Analysis; Machine Learning in Genomics; Single Cell RNA-seq; Machine Learning in Singl
版次1
doihttps://doi.org/10.1007/978-981-97-6703-8
isbn_softcover978-981-97-6702-1
isbn_ebook978-981-97-6703-8Series ISSN 2191-530X Series E-ISSN 2191-5318
issn_series 2191-530X
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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发表于 2025-3-21 22:53:01 | 显示全部楼层
2191-530X 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 c
发表于 2025-3-22 04:10:27 | 显示全部楼层
Dimensionality Reduction and Clustering,nderlying biological structures. The chapter details PCA and t-SNE algorithms, their applications, and software tools, providing Python-based case studies to demonstrate their practical implementation in scRNA-seq data analysis.
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Introduction to Single-Cell RNA-seq Data Analysis, single-cell sequencing technologies, the critical impact of scRNA-seq, and the powerful role of machine learning in overcoming analytical challenges, thereby facilitating advancements in personalized medicine and targeted therapies.
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