| 1 | 9-Sep | Class overview | | | ppt pdf | | Profs. Roy/Gitter |
| 2 | 14-Sep | Background | Graph theory | Molecular networks | ppt pdf | (1) Life and its molecules; (2) Topology of molecular networks | Prof. Roy |
| 16-Sep | | Probability theory | | pptx pdf | | Prof. Gitter |
| 3 | 21-Sep | Representing and learning networks from data | Bayesian network | Gene network inference | ppt pdf | (1) Markowetz and Spang (optional) (2) Friedman et al (3) Sparse candidate | Prof. Roy |
| 23-Sep | | Dependency networks | Gene network inference | ppt1 pdf1 ppt2 pdf2 | (1) Module networks (2) GENIE3 | Prof. Roy |
| 4 | 28-Sep | | Incorporating priors in Bayesian networks | Integrative network inference | ppt pdf | (1) Werhli et al (2) Cancer signaling and DBN | Prof. Roy |
| 30-Sep | | Incorporating priors in Dependency networks | Integrative network inference | ppt pdf | (1) Inferelator (2) (optional) iRafNet | Prof. Roy |
| 5 | 5-Oct | | Network inference with single cell data | | ppt pdf | (1) PIDC; (2)SCENIC | Prof. Roy |
| 7-Oct | Context-specificity and dynamics of networks | Dynamic models & non-stationary DBNs | Representing dynamics in molecular networks/development | pptx pdf | nsDBN | Prof. Gitter |
| 6 | 12-Oct | | I-O Hidden Markov Models | Integrating TF-DNA interactions with time-series expression | pptx pdf notes | DREM | Prof. Gitter |
| 14-Oct | | I-O Hidden Markov Models | | | | Prof. Gitter |
| 7 | 19-Oct | | Multi-task learning & GGMs | Tissue-specific networks | pptx pdf | GNAT | Prof. Gitter |
| 21-Oct | Deep learning in network biology | Network embedding and representation learning | Gene function prediction | pptx pdf | (1) Representation learning review (2) node2vec | Prof. Gitter |
| 8 | 26-Oct | | Graph neural networks 1 | Protein-protein and protein-ligand interactions | pptx pdf | (1) Distill intros (2) Wu et al | Prof. Gitter |
| 28-Oct | | Graph neural networks 2 | Drug discovery | pptx pdf | | Prof. Gitter |
| 9 | 2-Nov | | Graph generation | Synthetic biology | pptx pdf | MolGAN | Prof. Gitter |
| 4-Nov | Topological properties of graphs | Degree distribution, modularity motifs | Design principles of biological networks | pptx pdf | (1) Barabasi and Oltvai review (2) Girvan-Newman Algorithm | Prof. Roy |
| 10 | 9-Nov | | Spectral and Louvain clustering | Finding modules in networks | pptx pdf | (1) Louvain clustering (2) Module detection challenge | Prof. Roy |
| 11-Nov | | Dynamic network modules | | pptx pdf | | Prof. Roy |
| 11 | 16-Nov | Graph alignment | Spectral methods for alignment | Alignment of Protein-protein interaction networks | pptx pdf | (1) PathBLAST (2) IsoRank | Prof. Roy |
| 18-Nov | | Matrix factorization based alignment | Alignment of Protein-protein interaction networks | pptx pdf | FUSE | Prof. Roy |
| 12 | 23-Nov | | Graph alignment for single cell datasets | Integrating scOmics data | pptx pdf | (1) SCANORAMA (2) LIGER | Prof. Roy |
| 25-Nov | Thanksgiving | | | | | |
| 13 | 30-Nov | Network-based interpretation and integration of datasets | Graph diffusion and random walks | Disease gene prediction/gene prioritization | pptx pdf | GeneWanderer | Prof. Gitter |
| 2-Dec | | Graph diffusion | Interpreting cancer mutations | pptx pdf | HotNet | Prof Gitter |
| 14 | 7-Dec | | Steiner forest/integer programs | Data integration | pptx pdf | (1) Omics Integrator (2) ILP | Prof. Gitter |
| 9-Dec | Projects | | | | | |
| 15 | 14-Dec | Projects | | | | | |