| Course Name | Advanced Bioinformatics |
| Course Code | 24AIM439 |
| Program | B.Tech. Artificial Intelligence (AI) and Data Science (Medical Engineering) |
| Semester | VI |
| Credits | 3 |
| Campus | Coimbatore |
Introduction Phenotype, Central and Peripheral Dogmas, Systems Biology, Human Genome, Databases in Molecular Biology, Genetics Background, Maps and Tour Guides, DNA Sequencing, Next-Generation Sequencing, Ethical, Legal and Social Issues, Genomes, Transcriptomes and Proteomes, Genomes of Prokaryotes and Eukaryotes, Sequence Alignment, Phylogeny
Structural Bioinformatics Principles of Protein Structure and Classification: Properties of Amino Acids and Peptide Bonds, Ramachandran Plot, Secondary Structures, Motifs and Folds, Protein Structure Visualization, Tools and Analysis of Protein Structures, Protein Structure Prediction and Modelling, Protein Databank, Concepts of B-factor and R-factor, Protein Structural Alignment and Superposition, Protein Fold Classification, CATH, SCOP and FSSP Databases
Algorithms in Bioinformatics Algorithms and Complexity, Exhaustive Search, Greedy Algorithms, Dynamic Programming Algorithms, Randomized Algorithms, Graph Algorithms, Dot Plots, Measures of Sequence Similarity, Applications of Multiple Sequence Alignment to Database Searching, DNA Digital Data Storage
Machine Learning Approach for Bioinformatics Machine-Learning Foundations: The Probabilistic Framework, Machine Learning Algorithms, Applications of Neural Networks in Bioinformatics, Hidden Markov Models, Stochastic Grammar, and Linguistics
Course Objectives:
Course Outcomes:
After completing this course, students should be able to
CO1: Analyze and interpret molecular biology and genetic data, applying principles of phenotypes and genomics.
CO2: Demonstrate proficiency in utilizing databases for molecular biology, understanding DNA sequencing techniques, and addressing ethical considerations in bioinformatics.
CO3: Apply principles of protein structure and classification to visualize, analyze, and predict protein structures using relevant tools and databases.
CO4: Implement various algorithms in bioinformatics for sequence analysis, database searching, and DNA digital data storage.
CO5: Utilize machine learning techniques for bioinformatics applications, including probabilistic frameworks, neural networks, hidden Markov models, and stochastic grammar.
CO-PO Mapping
|
PO/P SO |
PO 1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO 6 |
PO7 |
PO8 |
PO 9 |
PO 10 |
PO 11 |
PO 12 |
PSO 1 |
PSO2 |
PSO3 |
|
CO |
|||||||||||||||
|
CO1 |
1 |
3 |
1 |
– |
3 |
– |
– |
– |
2 |
2 |
– |
2 |
3 |
3 |
3 |
|
CO2 |
1 |
1 |
1 |
– |
3 |
– |
– |
– |
2 |
2 |
– |
2 |
3 |
3 |
3 |
|
CO3 |
1 |
1 |
1 |
– |
3 |
– |
– |
– |
2 |
2 |
– |
2 |
3 |
3 |
3 |
|
CO4 |
1 |
2 |
2 |
– |
3 |
– |
– |
– |
2 |
2 |
– |
2 |
3 |
3 |
3 |
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