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Course Detail

Course Name Advanced Bioinformatics
Course Code 24AIM439
Program B.Tech. in Artificial Intelligence (AI) and Data Science (DS) in Medical Engineering
Semester VI
Credits 3
Campus Coimbatore

Syllabus

Unit 1

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

Unit 2

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

Unit 3

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

Unit 4

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 Objectives:

  • To understand gene sequences, sequence matching and other related methods
  • To understand mathematical optimization concepts related to Bioinformatics
  • To understand algorithms related to Bioinformatics

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

Textbooks/References

  1. Lesk A., Introduction to Bioinformatics. United Kingdom: Oxford University Press, 2019.
  2. Bach, F., Brunak, S., Baldi, P., Baldi, P. P., Bioinformatics. Cambridge: Bradford, 2001.
  3. Mount, D. W, Bioinformatics: Sequence and Genome Analysis. Thailand: Cold Spring Harbor Laboratory Press, 2004.
  4. Baxevanis, A. D., Ouellette, B. F. F. Bioinformatics: a practical guide to the analysis of genes and proteins, 3rd ed. India: Wiley India Pvt. Limited, 2009.

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