Data Science Applications in Genomics and Drug Discovery

Participants who want to register are requested to take the screenings first, link for which is given under the “Eligibility & Fees and Screenings” tab

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

Description

Mode of workshop: HYBRID

Description:

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

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:

BTech/MTech/DD/PhD

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

Fees for the workshop:

Free For IITM students

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

Screenings:

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

https://docs.google.com/forms/d/e/1FAIpQLSdwHJ2c8K1gzNryZ1oW2A26AYzDVlfsheuCZOlx6SgplffOag/viewform

Certification

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

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