M.Sc. Bioinformatics

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Programme educational objectives

The M.Sc. (Bioinformatics) programme at SASTRA envisions creating a knowledge hub of graduates who can address key challenges in handling, analyzing and interpreting biological data. The specific objectives of the programme are:

• To impart fundamental concepts and principles of biology and techniques required for effective analysis and interpretation of biological data.
• To provide a broad base of basic bioinformatics concepts and skills and an in-depth knowledge of at least one area of biology including understanding of biological data generation technologies
• To inculcate a sense of scientific curiosity and self-learning abilities to make them life-long learners.
• To create individuals who possess ability to effectively communicate with a range of audience possessing varying degrees of scientific knowledge
• To develop interpersonal skills to work as a team in a multidisciplinary front to accomplish a common goal
• To equip the graduates with time and project management capabilities
• To create ethical professionals with social responsibility and legal awareness

 

Programme learning outcomes

Upon completion of the programme, the graduates will be able to

• Explain the role of bioinformatics in science and technology.
• Apply bioinformatics tools to analyze and interpret biological data.
• Develop efficient repositories and tools for biological data sharing.
• Employ computational tools to provide insights and solutions into biological problems.
• Work in a multidisciplinary team with effective communication and interpersonal skills.
• Contribute to the welfare of the society with ethical and environmental consciousness.

 

M. Sc.  - Bioinformatics
(For students admitted from 2020 – 21)
Scheme of Study

I Semester (26 credits) 

Course Code	Course Name	No of Contact Hours / Week			Credits
		L	T	P
BIN101	Introduction to Bioinformatics	3	0	2	4
BIN535	Physical Biology	4	1	0	5
BIN536	Scripting for Biological Data Analysis	2	1	2	4
BIN537	Molecular Structural Biology	4	0	0	4
INT413	RDBMS, SQL and Visualization	3	1	0	4
INT103	Database management systems laboratory lab	0	0	2	1
MAT445	Probability and Statistics using R	3	0	2	4
TOTAL		19	3	8	26

II Semester (26 Credits) 

Course Code	Course Name	No of Contact Hours / Week			Credits
		L	T	P
BIN543	Computational Chemical Modelling	4	0	0	4
BIN538	Genetics, Genomics & Proteomics	4	1	0	5
BIN304	Python Programming for Biologists	2	1	2	4
BIN549	Introduction to Data mining & Machine Learning for Bioinformatics	1	2	2	4
BIN5YZ	Elective 1	3	0	0	3
BIN5YZ	Elective 2	3	1	0	4
BIN539	Contemporary Topics in Bioinformatics	0	0	2	1
BIN544	Computational Chemical Modelling Laboratory	0	0	2	1
TOTAL		17	5	8	26

III Semester (22 credits) 

Course Code	Course Name	No of Contact Hours / Week			Credits
		L	T	P
BIN305	Drug Design	3	0	0	3
BIN311	Systems Modelling	3	0	0	3
BIN540	Next Generation Sequencing Techniques, Application and Data Analytics	4	0	0	4
BIN5YZ	Elective 3	3	0	2	4
BIN307	Drug Design Laboratory	0	0	2	1
BIN541	Systems Modelling Lab	0	0	2	1
BIN542	Omics Data Analysis Laboratory	0	0	4	2
BIN599	Project Phase I	0	0	4	2
MAN106	Research Methodology & IPR	2	0	0	2
		15	0	14	22

IV Semester (16 Credits) 

Course Code	Course Name	No of Contact Hours / Week			Credits
		L	T	P
BIN600	Project work & Viva Voce	0	0	32	16
		0	0	32	16

 

List of Electives

Elective 1: Biophysical Techniques/ Microbial Genomics and Case Studies

Elective 2: Biomolecular Crystallography/ Computational Molecular Evolution

Elective 3: Integrative Structural Biology/ Cheminformatics

Approved list of electives

1. Integrative Structural Biology
2. Biophysical Techniques
3. Biomolecular Crystallography
4. Computational Molecular Evolution
5. Microbial Genomics and Case Studies
6. Immunoinformatics
7. Cheminformatics
8. Computational Neuroscience