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Course Detail

Course Name Bioinformatics
Course Code 24MMD214
Program B. Sc. Honors (with Research) in Molecular Medicine
Semester 4
Credits 3
Campus Kochi

Syllabus

Preamble

Bioinformatics is a discipline that integrates different sub-disciplines of informatics, chemistry, physics, molecular biology, biochemistry and molecular medicine. This course aims at understanding the molecular basis of life by looking into genes, proteins and small molecules on the basis of different biological databases, sequence algorithms, computational biology and its related software. Latest trend in introduction of machine learning, artificial intelligence and its applications addressed.

Unit 1

History of Bioinformatics. The notion of Homology. Sequence Information Sources, NCBI, EMBL, GENBANK, Entrez, Uniprot, Prosite, Understanding the structure of each source and using it on the web. Searching Databases: Integrated databases.

Unit 2

Sequence Similarity Searches-BLAST, FASTA, Data Submission. Genome Annotation: Consensus sequence, Sequence Pattern and repeat finding, Gene identification tools; Protein Information Sources, SWISSPROT, TREMBL, Protein data bank, Understanding the structure of each source and using it on the web. Metabolomics and pathway databases.

Unit 3

Protein sequence and Phylogeny analysis, Detecting Open Reading Frames, Outline of sequence assembly, Mutation/Substitution matrices, Pairwise sequence alignments, Introduction to BLAST, using it on the web, Interpreting results., Introduction to BLAST, using it on the web, Interpreting results. Multiple sequence alignments: ClustalOmega, XML and its applications in biochemoinformatics.

Unit 4

Data mining, Introduction to machine learning and its applications. Introduction to Linux commands. Artificial intelligence concepts and its application in bioinformatics studies.

Unit 5

(1) Sequence information database resource;

(2) Understanding and use of various web resources: EMBL, Genbank, Unigene, Protein information resource (PIR);

(3) Understanding and using: PDB, Swissprot, TREMBL;

(4) Pair wise sequence alignment and interpretation of results;

(5) Data mining and small molecule structure optimization; Basic linux commands.

(6) Macromolecular structure visualization interaction and function interpretation.

(7) Multiple sequence alignment and visualization

Objectives and Outcomes

Course Outcomes (CO):

CO1 : Basic concepts in biological sequence databases, using it on the web, and integrated database information.

CO2 : Fundamentals of biological sequence analysis, sequence pattern matching and recognition and pairwise sequence alignment, understanding the sequence structure-function relationships.

CO3 : Understanding the protein sequence, Protein evolution and Phylogenetic tree analysis, Functioning of BLAST software and its statistical parameters significance in pairwise sequence alignment.

CO4: Basic concepts in Big data analysis and its web applications in drug discovery program. Introduction to machine learning techniques and its medical case studies. Knowledge in Linux environment and its commands.

CO5 : Practical application of different biologically important software, protocols and computational strategies taught and applied in different molecular medicine cases. 

Program Outcomes (PO)

PO1: Bioscience Knowledge

PO2: Problem Analysis

PO3: Design/Development of Solutions

PO4: Conduct Investigations of complex problems

PO5: Modern tools usage

PO6: Bioscientist and Society

PO7: Environment and Sustainability

PO8: Ethics

PO9: Individual & Team work

PO10: Communication

PO11: Project management & Finance

PO12: Lifelong learning

c

PO1

PO2

PO3

PO4

PO5

PO6

PO7

PO8

PO9

PO10

PO11

PO12

C O

CO 1

3

2

2

1

2

2

–

–

1

1

–

2

CO 2

3

2

2

1

2

2

–

–

2

1

–

2

CO 3

3

2

2

2

3

2

–

–

2

1

–

2

CO 4

3

2

2

2

3

2

–

–

2

1

–

2

CO 5

3

2

2

2

3

2

–

–

2

1

–

2

 

3 = High Affinity, 2 = Medium Affinity, 1 = Low Affinity, – = No Affinity

Program Specific Outcomes (PSO)

PSO 1 – Chemical and physical basis of biology

PSO 2 -Computational science in biology and medicine

PSO 3 -Biochemical and physiological complexity in biology and medicine

PSO 4 -Molecular technology in biology and medicine

PSO 5 – Cell based approaches in diagnosis and therapy

PSO 6 -Microorganisms in medicine

PSO 7 -Nanoscale entities and its significance in medicine

PSO 8 – Tissue architecture engineering in medicine

PSO 9 – Compounds as drugs and its efficacy

PSO 10 – Bioinformatics and artificial intelligence in medicine

PSO 11 –Technology in personalizing medicine

PSO 12 – Protein structural complexity in medicine

PSO 13 – Projecting science and medicine to public

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PSO1

PSO2

PSO3

PSO4

PSO5

PSO6

PSO7

PSO8

PSO9

PSO10

PSO11

PSO12

PSO13

C O

CO 1

2

3

2

2

–

1

–

–

1

2

1

2

–

CO 2

2

3

2

2

–

1

–

–

2

2

1

3

–

CO 3

2

3

2

2

–

1

–

–

2

3

2

2

–

CO 4

2

3

2

2

–

1

–

–

2

3

2

2

–

CO 5

2

3

2

2

–

1

–

–

2

2

2

3

–

Evaluation Pattern

Internal Assessment – 50% 

Periodical 1 

Exam 

20% 

Periodical 2 

Exam 

20% 

Continuous Assessment 

Assignment/Test/Quiz

10% 

50%

End Semester Examination- 50% 

Theory Exam 

50% 

50%

Total

100%

Text Books / References

(1) Bioinformatics: Genes, Proteins and Computers By Christine Orengo, David Jones, Janet Thornton, 2002 by Taylor & Francis, 320 Pages.

(2) Mount D W, “Bioinformatics Sequence and Genome Analysis”, CBS Publishers & Distributors (2003), ISBN: 8123909985.

(3) Practical Bioinformatics, by Michael Agostino, 2013, ISBN 9780815344568.

(4) Artificial Intelligence in Drug Discovery, Editor: Nathan Brown, Copyright year 2021; Print ISBN 978-1-78801-547-9

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