| Serial no. | Lecture nos. | Topics | Instructor | Slides |
| 1 | 1–2 | Introduction to Cellular and Molecular Biology | SA & KKS | Overview; Introduction to Biology |
| 2 | 3–4 | Introduction to Evolution; Modelling Evolution | SA & KKS | Introduction; Genetic Algorithms; Quasispecies |
| 3 | 5 | Discussion session on evolution | — | |
| 4 | 6–7 | The Data Revolution: Genomics/Transcriptomics/Proteomics | SA | DNA sequencing; Gene/Protein expression & interactions |
| 5 | 8–9 | Introduction to Signal Processing and Random Processes | KKS | Fourier Analysis; Entropy and Correlation; Probability Distributions |
| 6 | 10 | Hidden Markov Models for Gene Identification | SA | |
| 7 | 11–14 | Genomic Signal Processing | KKS | DNA Periodicity; Gene Coding Regions: Fourier Analysis; Gene Coding Regions: Information Theory; Origin of Replication – I; DNA Phylogeny; DNA Randomness |
| 8 | 15 | Discussion session on genomic signal processing | — | |
| 9 | 16–18 | Primer on networks; Protein interaction networks | SA | Date and Party hubs |
| 10 | 19–21 | Regulatory & signaling networks, motifs, and dynamics | K. Sriram; SA | Systems Biology – Signaling Motifs |
| 11 | 22–23 | Student presentations: Mini project 1 | — | |
| 12 | 24 | Evolvability and Learning | SA | Evolvability as Learnability |
| 13 | 25–26 | Large-scale network modelling and inference | SA | Dynamics and Inference on Biological Networks; Learning Predictive Models of Gene Dynamics |
| 14 | 27 | Discussion session on network biology | — | |
| 15 | 28 | Student presentations: Mini project 2 | — |