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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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

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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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