Executive Development Programme Single-Cell RNA Analysis for Scientists
-- ViewingNowThe Executive Development Programme in Single-Cell RNA Analysis is a certificate course tailored for scientists seeking to delve into the cutting-edge field of single-cell analysis. This programme emphasizes the importance of understanding gene expression at the single-cell level, enabling learners to tackle complex biological questions with unprecedented resolution.
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⢠Single-Cell RNA Sequencing (scRNA-seq) Fundamentals: An introduction to the basic principles, methods, and applications of scRNA-seq in scientific research.
⢠Library Preparation and Sequencing Technologies: Detailed exploration of the most common library preparation methods and sequencing platforms used in scRNA-seq experiments.
⢠Data Analysis and Processing: Comprehensive review of the bioinformatics tools and techniques required to analyze and process scRNA-seq data, including quality control, normalization, and filtering.
⢠Dimensionality Reduction and Clustering: Examination of various dimensionality reduction and clustering algorithms for visualizing and interpreting scRNA-seq data, including t-SNE, UMAP, and PCA.
⢠Differential Expression Analysis: Instruction on statistical methods and software tools for identifying differentially expressed genes between different cell populations in scRNA-seq data.
⢠Cell Type Identification and Annotation: Techniques for identifying and annotating specific cell types in scRNA-seq data, including the use of reference atlases and machine learning algorithms.
⢠Trajectory Analysis and Pseudotime Inference: Overview of methods for reconstructing differentiation trajectories and inferring the temporal dynamics of cellular processes in scRNA-seq data.
⢠Integrative Analysis of Multi-omic Data: Exploration of techniques for integrating scRNA-seq data with other types of omics data, such as genomic, epigenomic, and proteomic data, to gain a more comprehensive understanding of cellular systems.
⢠Practical Applications and Case Studies: Discussion of real-world applications and case studies of scRNA-seq in various scientific fields, including immunology, neuroscience, and cancer research.
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