About
This DeepScience-powered, self-paced certificate course delivers a structured journey through the fast-evolving domain of transcriptomics—from RNA sequencing (RNA-seq) fundamentals to cutting-edge single-cell transcriptomics and spatial gene expression technologies. Participants will explore how transcriptomic data unlocks insights into gene regulation, disease biomarkers, and precision medicine.
Designed with real-world application in mind, this course bridges molecular biology with computational genomics. Through expert-led lectures, case studies, and tool-based walkthroughs, you’ll gain actionable skills in biological data science and modern bioinformatics workflows.
Aim
To build interdisciplinary expertise in transcriptomic sciences, enabling participants to:
- Decode gene expression dynamics.
- Apply AI-ready bioinformatics pipelines.
- Transition into cutting-edge biotech and research roles.
Program Objectives
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Grasp core principles of RNA biology and transcriptome profiling.
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Master RNA extraction, sequencing workflows, and data preprocessing.
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Utilize industry-standard tools for single-cell data analysis.
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Interpret transcriptomic outputs in disease modeling and therapeutic targeting.
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Develop a research-ready mindset and pipeline in DeepTech biology.
Program Structure
Week 1: Transcriptomics in System Biology
- RNA Extraction, QC & Sequencing Technologies
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RNA-seq Data Processing & Quality Control
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Transcriptomics Software: FASTQC, STAR, Kallisto
Week 2: RNA-seq Data Analysis
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Read Mapping & Genome Annotation (using HISAT2, Ensembl)
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Quantification of Gene Expression (TPM, FPKM, raw counts)
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Data Normalization Techniques for Transcriptomic Integrity
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Statistical & Machine Learning Approaches to Differential Expression Analysis
Week 3: Single Cell Transcriptomics
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Introduction to Single Cell RNA-seq (10x Genomics, Smart-seq2)
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Protocols for Single Cell Library Prep & Barcoding
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Processing Pipelines: Cell Ranger, Seurat, Scanpy
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Visualizing Cell Clusters & Gene Markers (UMAP, t-SNE)
Week 4: Advanced Transcriptomic Applications
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Spatial Transcriptomics & Tissue Mapping Technologies
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Multi-Omics Integration: Proteomics, Metabolomics & RNA-seq
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Translational Case Studies in Cancer, Neuroscience, and Immunology
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DeepTech Trends: AI in Transcriptomics, Synthetic Biology Intersections
Intended For
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Life science graduates, postgraduates, and PhD students in biotech, genetics, or bioinformatics
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Researchers, lab professionals, and R&D executives in genomics & molecular diagnostics
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Medical professionals exploring precision medicine, genomic data interpretation, and translational bioinformatics
Program Outcomes
- Comprehensive expertise in RNA-seq and single-cell transcriptomics
- Proficiency in cutting-edge tools like Seurat, DESeq2, Cell Ranger, and Scanpy
- Ability to design, analyze, and visualize transcriptomic experiments
- Readiness for advanced roles in DeepTech-driven biotech, computational biology, and genomics research