chem.sastra.eduBioinformatics
Program Educational Objectives (PEO)
The B.Tech. Bioinformatics program at SASTRA envisions creating a knowledge hub of graduates who can address key challenges in handling, analyzing and interpreting biological data by integrating mathematics, information technology and biology.
The programme education objectives of B. Tech. Bioinformatics degree programme are:
- To impart fundamental concepts and principles of science and engineering
- To provide a broad base of knowledge in information technology, mathematics and biology and in-depth knowledge of at least one area of biology and understanding of biological data generation technologies
- To equip students with ability to combine biology, information technology and mathematics towards problem solving.
- 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
Program Specific Outcomes (PSO):
Upon completion of the program, the graduates will be able to,
- Apply the broad base of knowledge in information technology, mathematics, biology and computational tools for biological data generation and solving problems of significant academic/ industrial interest
- Create biological data repositories, web applications and tools/algorithms utilising multimodal data including from omics technologies and advancing biomedical data science
- Build, simulate and interpret dynamic models of complex biological systems furthering basic and applied research
- Work in a multidisciplinary team with effective communication and interpersonal skills to accomplish a common goal while keeping in mind professional ethics, economics, sustainability and society
B. Tech. in Bioinformatics
(For students admitted from 2019 –20)
Semester I (25 Credits)
|
Course Code |
Course Name |
No of Contact Hours / Week |
Credits |
||
|
L |
T |
P |
|||
|
ENG101R01/ BIT101R01 |
Technical Communication Biology for Engineers |
1 |
0 |
2 |
2 |
|
2 |
0 |
0 |
|||
|
MAT101R01 |
Engineering Mathematics & I |
3 |
1 |
0 |
4 |
|
CSE101 |
Problem Solving & Programming in C |
3 |
0 |
2 |
4 |
|
PHY101R01/ CHY101 |
Engineering Physics / Engineering Chemistry |
3 |
0 |
2 |
4 |
|
3 |
0 |
2 |
4 |
||
|
EEE101 / EIE101R01 |
Basic Electrical Engineering / Basic Electronics Engineering |
2 |
0 |
2 |
3 |
|
2 |
0 |
2 |
3 |
||
|
CIV101/ MEC101 |
Basic Civil Engineering / Basic Mechanical Engineering |
2 |
0 |
2 |
3 |
|
2 |
0 |
2 |
3 |
||
|
CIV102 / CIV103 |
Engineering Mechanics / Engineering Graphics |
2 |
1 |
0 |
3 |
|
1 |
0 |
4 |
3 |
||
|
MEC102 |
Introduction to Engineering Design |
2 |
0 |
0 |
2 |
|
TOTAL |
Group I(Technical Communication, Physics, Electrical, Civil, Mechanics & Design) |
18 |
2 |
10 |
25 |
|
Group II (Biology, Chemistry, Electronics, Mechanical & Graphics) |
15 |
1 |
14 |
23 |
|
Semester II (23 Credits)
|
Course Code |
Course Name |
No of Contact Hours / Week |
Credits |
||
|
L |
T |
P |
|||
|
ENG101R01/ BIT101R01 |
Technical Communication Biology for Engineers |
1 |
0 |
2 |
2 |
|
2 |
0 |
0 |
|||
|
MAT102R01 |
Engineering Mathematics & II |
3 |
1 |
0 |
4 |
|
CSE201 |
Object Oriented Programming in C++ |
3 |
0 |
2 |
4 |
|
PHY101 R01/ CHY101 |
Engineering Physics / Engineering Chemistry |
3 |
0 |
2 |
4 |
|
3 |
0 |
2 |
4 |
||
|
EEE101 / EIE101R01 |
Basic Electrical Engineering / Basic Electronics Engineering |
2 |
0 |
2 |
3 |
|
2 |
0 |
2 |
3 |
||
|
CIV101/ MEC101 |
Basic Civil Engineering / Basic Mechanical Engineering |
2 |
0 |
2 |
3 |
|
2 |
0 |
2 |
3 |
||
|
CIV102 / CIV103 |
Engineering Mechanics / Engineering Graphics |
2 |
1 |
0 |
3 |
|
1 |
0 |
4 |
3 |
||
|
MEC102 |
Introduction to Engineering Design |
2 |
0 |
0 |
2 |
|
TOTAL |
Group I (Biology, Chemistry, Electronics, Mechanical, &Graphics) |
15 |
1 |
14 |
23 |
|
Group II (Technical Communication, Physics, Electrical, Civil, Mechanics & Design) |
18 |
2 |
10 |
25 |
|
Semester III (24 Credits)
|
Course Code |
Course Name |
Hours / Week |
Credits |
||
|
L |
T |
P |
|||
|
MAT201 |
Engineering Mathematics - III |
3 |
1 |
0 |
4 |
|
BIT108 |
Biological Sciences - I |
3 |
0 |
0 |
3 |
|
BIN101 |
Introduction to Bioinformatics |
3 |
0 |
2 |
4 |
|
ICT101 |
Data Structures & Algorithms |
4 |
0 |
0 |
4 |
|
INT204 |
Linux & PERL |
3 |
0 |
2 |
4 |
|
INT102 |
Database Management systems |
3 |
0 |
0 |
3 |
|
BIT109 |
Biological Sciences Laboratory - I |
0 |
0 |
2 |
1 |
|
INT103 |
Database Management systems Laboratory |
0 |
0 |
2 |
1 |
|
TOTAL |
19 |
1 |
8 |
24 |
|
Semester IV (23 Credits)
|
Course Code |
Course Name |
Hours / Week |
Credits |
||
|
L |
T |
P |
|||
|
MAT301 |
Engineering Mathematics & IV |
3 |
1 |
0 |
4 |
|
BIT110 |
Biological Sciences & II |
3 |
0 |
0 |
3 |
|
BIN201 |
Structural Bioinformatics |
2 |
1 |
2 |
4 |
|
BIN202 |
Algorithms in Bioinformatics |
2 |
1 |
2 |
4 |
|
BIN304 |
Python Programming for Biologists |
2 |
1 |
2 |
4 |
|
BIN309/BIN313 |
Department Elective & 1: Clinical Informatics /Microbial Genomics |
3 |
0 |
0 |
3 |
|
BIT111 |
Biological Sciences Laboratory - II |
0 |
0 |
2 |
1 |
|
TOTAL |
15 |
4 |
8 |
23 |
|
Semester V (22 Credits)
|
Course Code |
Course Name |
Hours / Week |
Credits |
||
|
L |
T |
P |
|||
|
MAT306 |
Probability & Biostatistics |
3 |
1 |
0 |
4 |
|
CHY225 |
Medicinal Chemistry |
2 |
1 |
0 |
3 |
|
BIN301 |
Molecular Modelling |
2 |
1 |
0 |
3 |
|
BIN206 |
Fundamentals of Genomics & Proteomics |
3 |
0 |
0 |
3 |
|
BIN208 |
Web Technologies for Bioinformatics |
3 |
0 |
2 |
4 |
|
BINXYZ |
Department Elective & 2 |
3 |
0 |
0 |
3 |
|
BIN302 |
Molecular Modelling Laboratory |
0 |
0 |
2 |
1 |
|
TNP101 |
Soft Skills & I |
0 |
0 |
2 |
1 |
|
TOTAL |
16 |
3 |
6 |
22 |
|
Semester VI (22 Credits)
|
Course Code |
Course Name |
Hours / Week |
Credits |
||
|
L |
T |
P |
|||
|
BIN401 |
Statistical Applications in Bioinformatics |
2 |
1 |
0 |
3 |
|
BIN303 |
Protein Engineering |
2 |
1 |
0 |
3 |
|
BIN209 |
Next Generation Sequencing Methods |
3 |
0 |
0 |
3 |
|
BIN203 |
Introduction to Data mining & Machine Learning for Bioinformatics |
1 |
2 |
0 |
3 |
|
BINXYZ |
Department Elective & 3 |
3 |
0 |
0 |
3 |
|
BINXYZ |
Department Elective & 4 |
3 |
0 |
0 |
3 |
|
BIN402 |
Statistical Methods in Bioinformatics Laboratory |
0 |
0 |
2 |
1 |
|
BIN210 |
Next Generation Sequencing Methods Laboratory |
0 |
0 |
2 |
1 |
|
BIN397 |
Seminar |
0 |
0 |
2 |
1 |
|
TNP102 |
Soft Skills II |
0 |
0 |
2 |
1 |
|
TOTAL |
14 |
4 |
8 |
22 |
|
Semester VII (20 Credits)
|
Course Code |
Course Name |
Hours / Week |
Credits |
||
|
L |
T |
P |
|||
|
BIN305 |
Drug Design |
3 |
0 |
0 |
3 |
|
BIN307 |
Gene expression Data Analysis |
3 |
0 |
0 |
3 |
|
INT414 |
Big Data Analytics in Bioinformatics & Healthcare |
3 |
0 |
0 |
3 |
|
BINXYZ |
Department Elective & 5 |
2 |
1 |
0 |
3 |
|
BINXYZ |
Department Elective & 6 |
2 |
1 |
0 |
3 |
|
BIN306 |
Drug Design Laboratory |
0 |
0 |
2 |
1 |
|
BIN308 |
Gene expression Data Analysis Laboratory |
0 |
0 |
2 |
1 |
|
BIN300 |
Mini Project |
0 |
0 |
4 |
2 |
|
MAN105 |
Professional ethics |
0 |
0 |
2 |
1 |
|
TOTAL |
13 |
2 |
10 |
20 |
|
Semester VIII (21 Credits)
|
Course Code |
Course Name |
Hours / Week |
Credits |
||
|
L |
T |
P |
|||
|
BIN400 |
Project Work & Viva Voce |
0 |
0 |
24 |
12 |
|
OEXXYZ |
Open Elective |
3 |
0 |
0 |
3 |
|
OEXXYZ |
Open Elective |
3 |
0 |
0 |
3 |
|
OEXXYZ |
Open Elective |
3 |
0 |
0 |
3 |
|
TOTAL |
9 |
0 |
24 |
21 |
|
Partial List of Proposed Electives
|
Course Code
|
Course Name |
Hours / Week |
Credits |
||
|
L |
T |
P |
|||
|
BIN309 |
Clinical informatics |
3 |
0 |
0 |
3 |
|
BIN310 |
Medical image processing & analysis |
2 |
1 |
0 |
3 |
|
BIN311 |
Systems Modelling |
3 |
0 |
0 |
3 |
|
BIN312 |
Cheminformatics |
3 |
0 |
0 |
3 |
|
BIN313 |
Microbial Genomics |
3 |
0 |
0 |
3 |
|
BIN314 |
Experimental structure data analysis |
2 |
1 |
0 |
3 |
|
BIN315 |
Immunoinformatics |
3 |
0 |
0 |
3 |
|
BIN316 |
Computational Neuroscience |
3 |
0 |
0 |
3 |
|
BIN317 |
Pharmacogenomics |
3 |
0 |
0 |
3 |
|
BIN318 |
Deep Learning Methods for Bioinformatics |
3 |
0 |
0 |
3 |
|
BIN319 |
Structural Genomics |
2 |
1 |
0 |
3 |
|
BIN320 |
Principles of Biological Network Science |
2 |
1 |
0 |
3 |
|
BIN321 |
Synthetic Biology |
2 |
1 |
0 |
3 |
Cluster & 1: Clinical Informatics / Cheminformatics / Immunoinformatics
Cluster & 2: Medical Image Processing and Analysis / Experimental structure data analysis / Deep Learning Methods for Bioinformatics
Cluster & 3: Systems Modelling / Principles of Biological Network Science / Synthetic Biology/Computational Neuroscience
Cluster & 4: Microbial Genomics / Pharmacogenomics / Structural Genomics
