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Machine Learning in Single-Cell RNA-seq Data Analysis

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 understan...

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Bibliografski detalji
Glavni autor: Raza, Khalid (Autor)
Autor kompanije: SpringerLink (Online service)
Format: Elektronički e-knjiga
Jezik:engleski
Izdano: Singapore : Springer Nature Singapore : Imprint: Springer, 2024.
Izdanje:1st ed. 2024.
Serija:SpringerBriefs in Computational Intelligence,
Teme:
Artificial intelligence.
Machine learning.
Quantitative research.
Artificial Intelligence.
Machine Learning.
Data Analysis and Big Data.
Online pristup:https://doi.org/10.1007/978-981-97-6703-8
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Sadržaj:
  • Chapter 1. Introduction to Single-Cell RNA-seq Data Analysis
  • Chapter 2. Preprocessing and Quality Control
  • Chapter 3. Dimensionality Reduction and Clustering
  • Chapter 4. Differential Expression Analysis
  • Chapter 5. Trajectory Inference and Cell Fate Prediction
  • Chapter 6. Emerging Topics and Future Directions.

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