Bioinformatics (Practical)

Paper Code: 
24BTE329
Credits: 
02
Contact Hours: 
60
Objective: 

The aim of this course is to provide practical training in bioinformatic methods including accessing major public sequence databases, use of different computational tools to find sequences, analysis of protein and nucleic acid sequences by various software packages.

 

Course Outcomes: 

Course

 

 

Course Outcomes

Learning and teaching strategies

Assessment Strategies

  
 

Course Code

Course Title

  

 

 

 

 

 

 

 

 

 

 

24BTE329

 

 

 

 

 

 

 

 

 

 

Laboratory VII: Bioinformatics

(Practical)

 

 

CO168: Perform text- and sequence-based searches and predict secondary and tertiary structures of protein/nucleotide sequences

CO169: Explain major steps in pairwise and multiple sequence alignment.

CO170: Appraise the tools used for mutation and analysis of the energy minimization of protein structures.

CO171: Identify and illustrate the various elements of Bioinformatics.

CO172: Discuss and defend the concepts of Bioinformatics and illustrate the exercises performed with appropriate methods and outcomes and maintain proper documentation of the same.

CO173: Contribute effectively in course-specific interaction

 

Approach in teaching:  Hands-on practical, demonstrations, simulations

 

 

Learning activities for the students:  Discussion,

Tutorials,

Assignments

Reading Journals

 

 

 

Class test, Semester end examinations, Quiz, Solving problems in tutorials, Assignments, Presentation, Individual and group projects

  

Experiments based on:

Bioinformatics

  1. Using NCBI and Uniprot web resources.
  2. Introduction and use of various genome databases.
  3.  Sequence information resource: Using NCBI, EMBL, Genbank, Entrez Swissprot/ TrEMBL, UniProt.
  4. Similarity searches using tools like BLAST and interpretation of results.
  5.  Multiple sequence alignment using ClustalW.
  6.  Phylogenetic analysis of protein and nucleotide sequences.
  7.  Use of gene prediction methods (GRAIL, Genscan, Glimmer).
  8.  Using RNA structure prediction tools.
  9.  Use of various primer designing and restriction site prediction tools.
  10.  Use of different protein structure prediction databases (PDB, SCOP, CATH).
  11.  Construction and study of protein structures using Deepview/PyMol.
  12. Homology modelling of proteins.
  13.  Use of tools for mutation and analysis of the energy minimization of protein structures.

 Use of miRNA prediction, designing and target prediction tools.

 

Academic Year: 
2024-2025
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