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AKTU Bioinformatics I (BBT503) Syllabus PDF – B.Tech 3rd Year
Bioinformatics I BBT503
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Official AKTU syllabus of Bioinformatics I (BBT503) for B.Tech 3rd Year – 4 credits, L-T-P 3-1-0. Read the unit-wise course content, course outcomes, evaluation pattern and recommended books online, or download the PDF.
Syllabus — Bioinformatics I
Download PDFBBT503 · 4 credits · L-T-P 3-1-0
Course Objectives
Teach the basic concept of Bioinformatics, databases & Sequence analysis.
Develop the understanding of sequence analysis.
Provide knowledge of scoring matrix and detection of functional sites etc.
To impart knowledge related to phylogenetic analysis protein structure prediction.
COURSE OUTCOMES (SIX): Upon completion of this course, the students will be able to:
| CO1 | Understand concepts and application of Bioinformatics, types of databases, sequence similarity, sequence patterns and profiles. |
| CO2 | Use sequence alignment techniques, database searching, pair wise and multiple sequence alignment using various tools. |
| CO3 | Understand scoring matrices and its types including PAM, BLOSUM series and matrices for nucleic acid and protein sequences. |
| CO4 | Apply phylogeny and its concepts in molecular evolution and different methods of Phylogenetic tree construction. |
| CO5 | Understand and apply the protein structure prediction and application of bioinformatics in drug designing. |
| CO6 | Identify and utilize various biomolecular sequence file formats such as GenBank, EMBL, FASTA, GCG, and others. |
CO-PO MAPPING (1 TO 3 SCALE)
| CO/PO | PO- 1 | PO- 2 | PO- 3 PO- 4 PO- 5 PO- 6 PO- 7 PO- 8 PO- 9 PO- 10 PO- 11 PO- 12 |
| CO-1 | 1 | 2 | 1 |
| CO-2 | 3 | 1 | 2 1 2 1 |
| CO-3 | 2 | 1 | 2 1 |
| CO-4 | 1 | 3 | 1 |
| CO-5 | 1 | 2 | 1 |
| CO-6 | 1 | 2 | 1 2 1 2 1 2 |
Reference Books
- D.W.Mount; Bioinformatics-Sequence and genome analysis; Cold Spring HarbourLab press.
- B.N.Mishra; Bioinformatics: Concept and application, Pearson Education (in press)
- O’ Reilly; Developing Bioinformatics computer skills-1stIndian edition, SPD publication.
- Anthony J.F. Griffiths et al; An introduction to genetic analysis, 1stEd
- Michael Starkey and Ramnath Elaswarapu; Genomics protocols, Humana press
| COURSE DETAILS: BIOINFORMATICS I | ||
| Unit | Content | Contact Hours |
| I | Introduction to Bioinformatics; Biological databases: Nucleotide databases, Protein databases, Specialized databases; Laboratory data submission and data retrieval; Various file formats for biomolecular sequences: Genbank, EMBL, FASTA, GCG, msf, nbrf-pir etc.; Basic concepts of sequence similarity: identity and homology, definitions of homologues, orthologues, paralogues; Sequence patterns and profiles | 8 |
| II | Sequence Alignment And Database Searching: Introduction, Evolutionary Basis of Sequence Alignment, Optimal alignment method, Statistical Significance of Alignment. Database searching Artifacts; Database similarity searching: FASTA, BLAST, Various versions of basic BLAST and FASTA, Advance version of BLAST: PHI-BLAST and profile-based database searches using PSIBLAST; Multiple sequence alignment: progressive method and Iterative method; Applications of pairwise and multiple sequence alignment; Tools for multiple sequence alignment: CLUSTALW and Pileup (Algorithmic concepts). | 7 |
| III | Scoring Matrices: Basic concept of a scoring matrix, Similarity and distance matrix, Substitution matrices: Matrices for nucleic acid and proteins sequences, PAM and BLOSUM series, Principles based on which these matrices are derived and Gap Penalty; Predictive Method using Nucleotide Sequence: Introduction, Marking repetitive DNA, Database search, Codon bias detection, detecting functional site in DNA. | 7 |
| IV | Phylogenetics: Phylogeny and concepts in molecular evolution; nature of data used in taxonomy and phylogeny; definition and description of Phylogenetic trees and various types of trees; Different methods of Phylogenetic tree construction: UPGMA and Fitch-Margoliash Algorithm; case studies in phylogenetic sequence analysis. | 8 |
| V | Protein identification based on composition, Physical properties based on sequence, Motif and pattern, Secondary structure (Statistical method: Chou Fasman and GOR method, Neural Network and Nearest neighbor method) and folding classes, specialized structure or features, Tertiary structures (Homology Modeling); Structure visualization methods (RASMOL, CHIME etc.); Protein Structure alignment and analysis. Application of bioinformatics in drug discovery and drug designing. | 10 |
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