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AKTU Fundamentals of Omics Lab (BBI552) Syllabus PDF – B.Tech 3rd Year
Fundamentals of Omics Lab BBI552
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- Semester 5
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Official AKTU syllabus of Fundamentals of Omics Lab (BBI552) for B.Tech 3rd Year – 1 credits, L-T-P 0-0-2. Read the unit-wise course content, course outcomes, evaluation pattern and recommended books online, or download the PDF.
Syllabus — Fundamentals of Omics Lab
Download PDFBBI552 · 1 credits · L-T-P 0-0-2
Course Outcomes
At the end of the course, the student will be able to:
| CO1 | Demonstrate knowledge of open biological databases and AI based tools. | K2 |
| CO2 | Retrieve and process genomic, transcriptomic, and proteomic data using web servers. | K3 |
| CO3 | Apply alignment, clustering, and prediction methods with AI support. | K3 |
| CO4 | Apply computational tools to identify protein structures, motifs, and gene expression patterns. | K3 |
| CO5 | Explain AI applications in healthcare and multi-omics integration. | K2 |
List of Experiments
- Retrieve DNA sequences from NCBI and visualize basic sequence features.
- Primer designing.
- Perform gene prediction using AUGUSTUS (web server demo).
- Explore mutation detection using DeepVariant demo dataset.
- Load RNA-Seq sample data in Galaxy and generate expression plots.
- Cluster transcriptomic data using Orange Data Mining (drag-and-drop).
- Retrieve protein sequences from UniProt and analyze domains using InterPro.
- Predict protein secondary structure using SOPMA/PSIPRED online tools.
- Phosphorylation site prediction using NetPhos.
- Peptide structural characterization by Bioinformatics tool.
- Identify motifs in protein sequences using HMMER web server.
- Map genes/proteins to pathways using KEGG Mapper.
- Run a simple neural network in Google Colab to classify DNA vs. protein sequences.
- Apply K-means clustering on demo gene expression data (Orange/Colab).
- Case study: Use Orange’s built-in healthcare dataset to train a decision tree classifier. Note: The instructor may add / delete / modify / tune experiments as required.
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