Unit 1
Introduction to genomics – functional genomics – gene – different genomics experimental technology (next-generation sequencing, CRISPR/Cas9 etc.) – programming in R
| Course Name | Genomics Data Science |
| Course Code | 23AID446 |
| Program | B.Tech in Artificial Intelligence and Data Science |
| Credits | 3 |
| Campus | Coimbatore , Amritapuri ,Faridabad , Bangaluru, Amaravati |
Introduction to genomics – functional genomics – gene – different genomics experimental technology (next-generation sequencing, CRISPR/Cas9 etc.) – programming in R
Data cleaning and processing – sequence alignment for gene analysis – gene expression analysis – differential gene expression – Pathway analysis and functional annotation – machine learning in genomics.
Comparative genomics – epigenomics – metagenomics – pharmacogenomics – gene regulatory network analysis.
Precision medicine and personalised genomics – Cancer genomics and analysis – Infectious disease genomics and analysis
Course Objectives
Course Outcomes
After completing this course, students will be able to
|
CO1 |
Design sequence assembly in Genomics Data Science. |
|
CO2 |
Develop the ability to apply advanced computational methods to analyse genomics data. |
|
CO3 |
Develop the ability to identify the main results from a genomics research study and interpret figures from primary research papers. |
|
CO4 |
Analyse genomics data and design simulation experiments and interpret results. |
CO-PO Mapping
|
PO/PSO |
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
PSO1 |
PSO2 |
PSO3 |
|
CO |
|||||||||||||||
|
CO1 |
3 |
3 |
3 |
3 |
3 |
2 |
1 |
– |
2 |
– |
1 |
3 |
3 |
– |
– |
|
CO2 |
3 |
3 |
3 |
3 |
3 |
2 |
1 |
– |
2 |
– |
1 |
3 |
3 |
3 |
2 |
|
CO3 |
3 |
3 |
3 |
3 |
3 |
2 |
– |
– |
2 |
– |
– |
3 |
2 |
3 |
2 |
|
CO4 |
3 |
3 |
3 |
3 |
3 |
2 |
1 |
– |
2 |
– |
– |
3 |
– |
2 |
3 |
Evaluation Pattern
|
Assessment |
Internal/External |
Weightage (%) |
|
Assignments (minimum 2) |
Internal |
30 |
|
Quizzes (minimum 2) |
Internal |
20 |
|
Mid-Term Examination |
Internal |
20 |
|
Term Project/ End Semester Examination |
External |
30 |
Text Books / References
“Bioinformatics: Sequence and Genome Analysis” by David Mount
“Genomics and Personalized Medicine: What Everyone Needs to Know” by Michael Snyder
“Practice Computing for Biologists” by Steven Haddock and Casey Dunn
“Bioinformatics and Functional Genomics” by Jonathan Pevsner
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