NPTEL Course: Algorithms in Computational Biology & Sequence Analysis | Prof. Chirag Jain IISc
Course Details
| Exam Registration | 189 |
|---|---|
| Course Status | Ongoing |
| Course Type | Elective |
| Language | English |
| Duration | 12 weeks |
| Categories | Computer Science and Engineering, Multidisciplinary, Computational Biology, Data Science, Artificial Intelligence |
| Credit Points | 3 |
| Level | Undergraduate/Postgraduate |
| Start Date | 19 Jan 2026 |
| End Date | 10 Apr 2026 |
| Enrollment Ends | 02 Feb 2026 |
| Exam Registration Ends | 20 Feb 2026 |
| Exam Date | 19 Apr 2026 IST |
| NCrF Level | 4.5 — 8.0 |
Decoding Life with Code: A Deep Dive into Algorithms for Computational Biology
In the era of big data, biology has undergone a seismic shift. Questions that once required years of lab work—like finding disease-causing mutations in a genome or tracing the evolutionary tree of life—can now be approached by analyzing vast digital datasets. This revolution is powered not by microscopes alone, but by sophisticated algorithms and data structures. A new 12-week NPTEL course, "Algorithms in Computational Biology and Sequence Analysis," taught by Prof. Chirag Jain from the Indian Institute of Science (IISc) Bangalore, is designed to equip the next generation of researchers and engineers with these very tools.
Course Overview: Bridging Computer Science and Modern Biology
This course provides a comprehensive overview of the fundamental algorithms and data structures essential for analyzing large-scale biological data. It is meticulously crafted for computer science, applied mathematics, and data science students who aspire to design cutting-edge algorithmic solutions for scientific challenges. Over 12 weeks, participants will move from core string algorithms to advanced topics like pangenome graphs and machine learning applications, gaining both theoretical knowledge and practical skills through hands-on programming exercises using real-world data, such as the SARS-CoV-2 genome.
Meet the Instructor: Prof. Chirag Jain
The course is led by Prof. Chirag Jain, an Assistant Professor and India Alliance Intermediate Fellow in the Department of Computational and Data Sciences at IISc Bangalore. Prof. Jain leads a research group focused on developing scalable algorithms and software for genomics. His distinguished academic path includes a PhD from Georgia Tech (awarded the College of Computing Dissertation Award) and post-doctoral research at the National Institutes of Health (NIH), USA. This blend of deep algorithmic expertise and real-world genomic application experience makes him an ideal guide for this interdisciplinary journey.
Who Should Enroll?
Intended Audience: Undergraduate and postgraduate students with a keen interest in developing fast, efficient algorithms and software for biology and genomics.
Prerequisites: A solid foundation is required, including:
- Elementary knowledge of discrete mathematics.
- Understanding of basic algorithms and data structures (sorting, searching, hashing, graph traversal).
- Programming proficiency in C, C++, Java, or Python.
Detailed 12-Week Course Layout
| Week | Topics Covered |
|---|---|
| Week 1-3 | Introduction & Strings: Molecular biology fundamentals, Z-algorithm, suffix arrays, suffix trees and their construction. |
| Week 4-5 | Pairwise Sequence Alignment: Dynamic programming for global/local alignment, edit distance, gap penalties, alignment significance. |
| Week 6-7 | Heuristic Alignment & Genome Reconstruction: BLAST-like heuristics, co-linear chaining, genome assembly as a shortest common superstring problem. |
| Week 8 | Graph Algorithms for Genomics: de Bruijn graphs, overlap graphs for modern genome assembly. |
| Week 9 | Evolution & Multiple Alignment: Algorithms for multiple sequence alignment and evolutionary tree construction. |
| Week 10 | Probabilistic & AI Models: Hidden Markov Models for gene finding, introduction to large language models for sequences. |
| Week 11 | Pangenome Graphs: Next-gen pangenome representations and sequence-to-graph alignment. |
| Week 12 | Frontier Research: Discussion of seminal and contemporary research papers in the field. |
Learning Resources and Industry Relevance
While no single textbook is mandatory, the course draws from classic and modern texts for further reading, including Algorithms on Strings, Trees, and Sequences by Gusfield and the recent Genome-Scale Algorithm Design. The skills taught are in high demand, with industry support from companies like Google Health and Strand Life Sciences that develop software for molecular biology and omics applications.
Why Take This Course?
This course is more than a syllabus; it's a gateway to a frontier field. It transforms abstract algorithmic concepts into powerful tools to answer profound biological questions. Whether your goal is to pursue research in computational genomics, contribute to the booming biotech industry, or simply understand the computational engine driving modern life sciences, this course offers the foundational knowledge and practical insight to get started. Enroll to learn not just how to write code, but how to write code that decodes the blueprint of life.
Enroll Now →