Online Certificate Course in Industrial Bioinformatics
We offer an integrative, multidisciplinary training program that encompasses biology using computational and quantitative methods. This program focuses on various databases, tools, and techniques that are central to computational biology. We would cover “Basic Bioinformatics” and “Drug Design” in detail. In the last two modules, we cover data analysis using “Biopython” and “Machine Learning” application on biological problems. This course is designed for undergraduate and postgraduate students. However, it would be equally beneficial for PhDs and post-doctoral candidates. This course would provide extensive hands-on and sufficient lectures from the expertise of different fields. An assignment would be provided to participants for better understanding. Instructors for this course are from industries and academia with rich experience in bioinformatics.
A student who has met the objectives of the course will be able to:
Understand : Fundamentals of Bioinformatics
Learn : Necessary bio-computational skills, data analytics strategies, established workflows, biological concepts to interpret the results and professional depiction of data.
Apply : Fundamental concepts and analytics strategies, while working on real-time projects based on research problems from diverse backgrounds like agriculture, healthcare, environmental sciences etc.
Duration of training : 45 Days (57 Hours)
Commencement of registration : 01st November, 2020
Commencement of programme : 08 January, 2021
Eligibility criteria : B. Tech / B. Sc / M. Sc / M. Tech / Ph. D
Domain : Industrial Bioinformatics
Certification : Pathfinder Research and Training Foundation
Fee : Rs.10000/- including GST
The entire training will be online and shall have following prerequisites:
- Participants must have access to the laptop/desktop with stable internet connection.
- Participants must possess a google account (email@example.com).
Schedule of programme Industrial Bioinformatics
|Days||6:00 PM - 7:00 PM||7:00 PM - 8:00 PM||8:00 PM - 9:00 PM|
|Day 1: Friday||Guest inauguration lecture||Introduction to bioinformatics, opportunities, and domains|
|Day 2: Saturday||Introduction to biological database||Sequence alignment theory||Practical session: Pairwise sequence alignment|
|Day 3: Sunday||Practical session: Multiple sequence alignment||Practical session: Protein motif & domain prediction||Gene prediction tools|
|Day 4: Friday||Practical session: Gene and promoter sequence||Phylogenesis hands-on|
|Day 5: Saturday||Protein structure basics||Protein databases||Secondary structure prediction hands-on|
|Day 6: Sunday||Tertiary structure prediction hands on||Tertiary structure prediction hands-on||Introduction to next generation sequencing|
|Day 7: Friday||Whole exome sequencing hands on||Whole exome sequencing hands-on|
|Day 8: Saturday||RNA-Seq hands on||RNA-Seq hands on||Assignment on basic bioinformatics|
|Day 9: Sunday||Guest lecture on drug design||What is in-silico drug design?||Databases used in drug design|
|Day 10: Friday||Molecular structure explanation & visualization||Docking session - hands-on|
|Day 11: Saturday||Docking Session-hands-on||Docking result interpretation||Binding energy & protein-ligand interaction study|
|Day 12: Sunday||Plotting interaction details||Plotting interaction details||Plotting interaction details|
|Day 13: Friday||QSAR hands on||QSAR hands on|
|Day 14: Saturday||Pharmacophore design||Pharmacophore design||Pharmacophore design|
|Day 15: Sunday||What is bio python. Installation of bio python||Basic concept of python-hands-on||Basic concept of python-hands on|
|Day 16: Friday||Operation on sequence object-hands on||Sequence record object hands on|
|Day 17: Saturday||Biological file handling||Biological file handling||Biological file handling|
|Day 18: Sunday||Assignment on biopython|
|Day 19: Friday||Guest lecture machine learning & data science||Installation of 'R'|
|Day 20: Saturday||Basic concept of 'R' data type, variables, operation||Data processing & Regression model using 'R'||Data Processing & Regression model using 'R'|
|Day 21: Sunday||Evaluation of regression model||Build machine learning models exercise: Random forest & SVM|
|Concluding day||Assignment on machine learning||Thank you note & certificate distribution|
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