Executive Development Programme Single-Cell RNA Analysis for BioTech
-- ViewingNowThe Executive Development Programme in Single-Cell RNA Analysis for BioTech is a certificate course designed to provide learners with comprehensive knowledge and skills in the rapidly evolving field of single-cell RNA sequencing. This program emphasizes the importance of understanding the principles, techniques, and applications of single-cell RNA analysis to drive innovation and tackle complex challenges in the biotechnology industry.
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Dรฉtails du cours
โข Single-Cell RNA Sequencing (scRNA-seq) Fundamentals: Introduction to scRNA-seq technology, its applications, and benefits in biotechnology and pharmaceutical research. Overview of different scRNA-seq platforms and protocols.
โข Sample Preparation and Library Construction: Detailed discussion on sample preparation techniques, quality control, and library construction for scRNA-seq. Explanation of unique molecular identifiers (UMIs) and barcoding strategies.
โข Data Analysis Workflows: Overview of computational tools and workflows for scRNA-seq data analysis. Emphasis on quality control, data normalization, and dimensionality reduction techniques.
โข Clustering and Cell Type Identification: Exploration of unsupervised and supervised clustering methods for scRNA-seq data. Techniques for identifying and annotating cell types, including marker gene analysis and gene expression patterns.
โข Differential Expression Analysis: Deep dive into statistical methods for detecting differentially expressed genes across cell populations. Explanation of false discovery rate (FDR) and multiple testing correction strategies.
โข Trajectory Inference and Pseudotime Analysis: Introduction to single-cell trajectory inference and pseudotime analysis methods. Understanding the role of these techniques in understanding cell differentiation and development.
โข Integrative Analysis of Multi-omics Data: Overview of integrating scRNA-seq data with other omics data, such as ATAC-seq, ChIP-seq, and proteomics data. Explanation of benefits and challenges of multi-omics data integration.
โข Data Visualization and Interpretation: Best practices for data visualization and interpretation in scRNA-seq data analysis. Discussion on visualization tools and techniques for effectively communicating results.
โข Ethical and Regulatory Considerations: Overview of ethical and regulatory considerations in scRNA-seq
Parcours professionnel
Exigences d'admission
- Comprรฉhension de base de la matiรจre
- Maรฎtrise de la langue anglaise
- Accรจs ร l'ordinateur et ร Internet
- Compรฉtences informatiques de base
- Dรฉvouement pour terminer le cours
Aucune qualification formelle prรฉalable requise. Cours conรงu pour l'accessibilitรฉ.
Statut du cours
Ce cours fournit des connaissances et des compรฉtences pratiques pour le dรฉveloppement professionnel. Il est :
- Non accrรฉditรฉ par un organisme reconnu
- Non rรฉglementรฉ par une institution autorisรฉe
- Complรฉmentaire aux qualifications formelles
Vous recevrez un certificat de rรฉussite en terminant avec succรจs le cours.
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Frais de cours
- 3-4 heures par semaine
- Livraison anticipรฉe du certificat
- Inscription ouverte - commencez quand vous voulez
- 2-3 heures par semaine
- Livraison rรฉguliรจre du certificat
- Inscription ouverte - commencez quand vous voulez
- Accรจs complet au cours
- Certificat numรฉrique
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