Course Code: CUBS2542
Course Title: BIOINFORMATICS
Credits: 4
Type: (3+1+0)
Course Overview:
This course provides an in-depth introduction to bioinformatics, focusing on the use of biological databases, sequence alignment techniques, and molecular phylogenetics. Through a combination of theoretical knowledge and practical exercises, students will learn to critically assess biological data and perform various bioinformatics analyses to infer evolutionary relationships.
Prerequisites:
  • Basic understanding of molecular biology and genetics.
  • Basic proficiency in computer usage and familiarity with bioinformatics tools.
Course Objectives:
  1. Comprehend the fundamental principles of biological databases, including their types, significance, and potential pitfalls. (L2)
  2. Understand sequence alignment techniques, including the evolutionary basis, scoring matrices, and the statistical significance of sequence alignments. (L3)
  3. Apply multiple sequence alignment methods and molecular phylogenetics concepts to analyze biological data and infer evolutionary relationships. (L4)
Course Learning Outcomes:
  • CO1: Critically assess the relevance and limitations of biological databases and effectively retrieve information from them. (L2)
  • CO2: Perform database similarity searches using tools like BLAST and FASTA and evaluate the significance of search results. (L3)
  • CO3: Independently conduct multiple sequence alignments and molecular phylogenetic analyses, including the application of distance-based and character-based methods, and evaluate the quality of phylogenetic trees, demonstrating their ability to analyze and interpret biological data in an evolutionary context. (L4)
CO-PO Mapping Matrix:
CO\PO PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12
CO1 3 2 2 1
CO2 3 3 2 2 3 2
CO3 2 3 3 3 3 2 2 2 3

L1 – Remember
L2 – Understand
L3 – Apply
L4 – Analyze
L5 – Evaluate
L6 – Create
SYLLABUS

Module 1: Introduction to Biological Databases
  • What Is a Database?
  • Types of Databases
  • Biological Databases
  • Pitfalls of Biological Databases
  • Information Retrieval from Biological Databases

Module 2: Pairwise Sequence Alignment
  • Evolutionary Basis
  • Sequence Homology versus Sequence Similarity
  • Sequence Similarity versus Sequence Identity
  • Methods
  • Scoring Matrices
  • Statistical Significance of Sequence Alignment

Module 3: Database Similarity Searching
  • Unique Requirements of Database Searching
  • Heuristic Database Searching
  • Basic Local Alignment Search Tool (BLAST)
  • FASTA
  • Comparison of FASTA and BLAST
  • Database Searching with the Smith-Waterman Method
  • Exercise:
    • Hypothesis: Heuristic search methods (BLAST, FASTA) always yield results comparable to exact methods (Smith-Waterman).
    • Exercise: Compare the results and computational efficiency of the same dataset’s heuristic and exact search methods.

Module 4: Multiple Sequence Alignment
  • Scoring Function
  • Exhaustive Algorithms
  • Heuristic Algorithms
  • Practical Issues
  • Exercise:
    • Hypothesis: Heuristic algorithms for multiple sequence alignment are as accurate as exhaustive algorithms.
    • Exercise: Compare alignments generated by heuristic and exhaustive algorithms and assess their accuracy against known reference alignments.

Module 5: Molecular Phylogenetics
  • Molecular Evolution and Molecular Phylogenetics
  • Terminology
  • Gene Phylogeny versus Species Phylogeny
  • Forms of Tree Representation
  • Why Finding a True Tree Is Difficult
  • Procedure
  • Distance-Based Methods
  • Character-Based Methods
  • Phylogenetic Tree Evaluation
  • Phylogenetic Programs
  • Exercise:
    • Hypothesis: All phylogenetic methods produce similar evolutionary trees.
    • Exercise: Generate phylogenetic trees using distance-based and character-based methods and compare their topologies and accuracy with known evolutionary relationships.

Text Book:
  • Xiong, Jin. Essential Bioinformatics. Cambridge University Press, 2006.
Module 1: Introduction to Biological Databases
Hours Session Type Topic Name Learning Outcome(s)
1 Theory What Is a Database? Understanding basic database concepts.
1 Theory Types of Databases Differentiating between various types of databases.
1 Theory Biological Databases Identifying specific biological databases.
1 Theory Pitfalls of Biological Databases Recognizing limitations and potential errors.
1 Theory Information Retrieval from Biological Databases Learning effective information retrieval techniques.
2 Theory Falsification Exercise Introduction Hypothesis: Biological databases contain comprehensive and error-free data. Examining potential errors.
3 Practice Using Biological Databases Hands-on practice retrieving data from various databases.
2 Project Project Planning and Setup Initial project setup and planning.
1 Assignment Presentation
Total Hours: 14 Hours
Module 2: Pairwise Sequence Alignment
Hours Session Type Topic Name Learning Outcome(s)
1 Theory Evolutionary Basis of Sequence Alignment Understand how sequence alignment is grounded in evolutionary principles.
1 Theory Sequence Homology vs Similarity Differentiate between homologous and similar sequences and their biological implications.
1 Theory Sequence Similarity vs Sequence Identity Interpret the difference between similarity and identity and their roles in alignment scoring.
2 Theory Methods of Pairwise Sequence Alignment (Global & Local) Gain knowledge of alignment strategies and algorithms like Needleman-Wunsch and Smith-Waterman.
1 Theory Scoring Matrices (PAM, BLOSUM) Understand how substitution matrices influence alignment results.
2 Theory Statistical Significance of Sequence Alignment Evaluate alignment results using statistical tools like E-value, bit score, and Z-score.
3 Practice Performing Pairwise Sequence Alignments Hands-on session using tools such as EMBOSS, BLAST, or Clustal Omega for real alignments.
2 Project Project Planning and Setup Designing and initializing a project using pairwise alignment for gene or protein comparison.
1 Assignment Presentation
Total Hours: 14 Hours
Module 3: Nucleotide Sequence Databases
Hours Session Type Topic Name Learning Outcome(s)
1 Theory Introduction to Nucleotide Sequence Databases Understand the structure, content, and functions of nucleotide sequence databases.
2 Theory GenBank, EMBL, and DDBJ Explore major public nucleotide databases and their data submission and retrieval formats.
2 Theory Structure of a GenBank Record Analyze fields such as locus, features, annotations, and references in a GenBank flat file.
2 Practice Searching and Retrieving Sequences from NCBI Hands-on experience using Entrez and NCBI tools to search, retrieve, and interpret nucleotide sequences.
2 Practice Using EBI and DDBJ Portals Familiarize with alternative nucleotide database interfaces and search tools provided by EBI and DDBJ.
2 Project Comparative Database Analysis Conduct comparative evaluation of GenBank, EMBL, and DDBJ based on structure, features, and accessibility.
1 Assignment Presentation
Total Hours: 12 Hours
Module 4: Protein Sequence Databases
Hours Session Type Topic Name Learning Outcome(s)
1 Theory Introduction to Protein Sequence Databases Explain the role and importance of protein sequence databases in bioinformatics.
2 Theory UniProtKB, Swiss-Prot, TrEMBL Distinguish between curated and automatically annotated protein databases and their features.
2 Theory PIR, PDB, and RefSeq Protein Explore additional protein resources, including structural and reference protein data repositories.
2 Practice Searching Protein Databases Perform database queries using UniProt, PIR, and NCBI protein interfaces.
2 Practice Understanding a UniProt Entry Analyze a protein record, including function, domains, GO terms, cross-references, and structure links.
2 Project Comparative Study on Protein Databases Evaluate various protein databases based on depth of annotation, accessibility, and scientific utility.
1 Assignment Presentation
Total Hours: 12 Hours
Module 5: Structure Databases
Hours Session Type Topic Name Learning Outcome(s)
1 Theory Introduction to Molecular Structure Databases Explain the significance of structure databases and types of molecular structures stored.
2 Theory Protein Data Bank (PDB) Describe the data model, file formats, and functional features of the PDB database.
2 Theory MMDB, SCOP, and CATH Differentiate structure classification systems and understand their hierarchical structure.
2 Practice Browsing and Downloading Structures from PDB and MMDB Retrieve and interpret structural data using online platforms such as RCSB PDB and NCBI MMDB.
2 Practice Visualization of Macromolecular Structures Visualize protein structures using molecular viewers such as PyMOL, RasMol, or Jmol.
2 Project Comparative Study on Structure Classification Databases Evaluate the SCOP and CATH classification systems in terms of coverage, depth, and utility.
1 Assignment Presentation
Total Hours: 12 Hours