Data Science Applications in Genomics and Drug Discovery

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SKU: IIT Madras | Dates: November 28 to December 9, 2022 Categories: ,


Mode of workshop:  HYBRID


The course is aimed at providing exposure to one of the biggest healthcare challenge of antimicrobial resistance the world is facing today with specific focus on how to address the same. The course structure includes utilizing pan-genomics and AI/ML driven approaches to identify potential drug targets for most critical pathogens. It is also important to note that microbes undergo rapid evolution when exposed to antibiotics and therefore the challenge is to understand a dynamically evolving system and identify its strengths and weaknesses to devise novel strategies like identification of previously unknown target space based on new mechanisms of bacterial survival under antibiotic exposure and use this knowledge to scan unexplored chemical space. The project-based components in this course are to identify novel target and inhibitor space for the most critical pathogens. The course entails introduction to machine learning, Python programming, network-based methods for target identification, comparative genomics for exploring novel target space, etc.


Session dates:  November 28  – December 9,  2022

Time:  8am to 5pm 

Last date of Registration:  November 20th, 2022

Profile of the Instructor(s)

Prof.Anshu Bhardwaj obtained her Ph.D. in Life Sciences (2008) from Centre for Cellular and Molecular Biology, Hyderabad. The focus of her Ph.D. thesis was on prioritizing Single Nucleotide Polymorphism (SNPs) in disease association studies to identify potential biomarkers. As a lead PI in the Open Source Drug Discovery project, She conceived, designed and implemented crowdsourcing as a tool to tackle challenging scientific problems (Connect to Decode project), which is considered a futuristic approach to drive big data scientific projects. Over years, Dr. Bhardwaj has published several prediction methods, databases and ontology based barcoding methods for genome variation data towards better understanding of genotype-phenotype correlations in addition to state-of-the-art interactome and reactome for Mycobacterium tuberculosis. She also writes popular science articles. She served as an Associate scientific advisor to Science Translational Medicine and is on the Editorial board of Frontiers in Systems Biology. She was selected as one of the young Innovator in India by UNDP and for International Visitor Leadership Program by US State Department.

Prof.Karthik Raman is an Associate Professor at the Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, IIT Madras. Karthik’s research group works on the development of algorithms and computational tools to understand, predict and manipulate complex biological networks. Broadly spanning computational aspects of synthetic and systems biology, key areas of research in his group encompass microbiome analysis, in silico metabolic engineering, biological network design and biological data analysis. Karthik also co-ordinates the Centre for Integrative Biology and Systems mEdicine (IBSE) at IIT Madras and is a core member of the Robert Bosch Centre for Data Science and Artificial Intelligence (RBC-DSAI). Karthik teaches courses on computational biology and systems biology at IIT Madras, and has also authored a textbook on Computational Systems Biology.

Detailed Schedule

Day 1 Introduction to the course – broad objectives 30 mins
NGS data formats and pre processing and assembly 1hr
Nanopore – Galaxy 1hr
Day 1 Genome annotation – basics, file formats and tools 1hr
RAST, Prokka 1hr
Assignment on Priority Pathogens
Day 2 Metagenome and Pangenome – definitions and tools 1hr
Metagenome – Galaxy 1hr30mins
Review of the assignments 2hrs
Day 3 Python for Biologists – I 1hr
Python for Biologists – II 3hrs
Review of the assignments 1hr
Day 4 Basics of drug discovery – I 1hr
Hands-on web-based resources & their use 1hr
Drug target identification – protein-protein interaction networks 1hr
Drug target identification – protein-protein interaction networks 1hr
Day 5 Drug target identification – Metabolic reconstruction 2hrs
Drug target identification – Metabolic reconstruction 2hrs
Review of the assignments 1hr
Day 6 ML for target prediction, inhibitor identification and prioritization 1hr
XGBoost 1hr
Drug repurposing – basics and introduction to network based inference 30 mins
Hands-on web-based resources & their use 30 mins
Day 7 Introduction to AMR, global and Indian Priority Pathogens (PP) 1hr
CARD, Galaxy-AMR 1hr
Pangenome and ML for target prediction in PP
Day 8 Review of the assignments 2hrs
Applying systems-level analysis for target prediction in PP
Day 9 Introduction to chemical structure presentation, ADMET, PAINS filters 1hr
Development of workflows following FAIR principles 1hr
Day 10 Demonstration of data from at least one PP 2hrs
Integration of ensemble approaches to understand AMR

Eligibility & Fees and Screenings

Background / prior courses recommended:

Interest/ experience in biology

Intended audience:


Previous exposure to computer programming will be helpful but not mandatory to take the course

Fees  for the workshop:

Free For IITM students

  1.              Rs. 5,000 + GST for online students
  2.              Rs. 18,000 + GST for industry – in person only
  3.              Rs. 10,000 + GST for in-person students.



Please fill the form below as a part of screenings  for registering in this workshop.



After successful completion of the course, a participation certificate will be awarded to each participant.


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