| 1 |
9-Sep |
Class overview |
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ppt pdf |
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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 |
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16-Sep |
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Probability theory |
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pptx pdf |
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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 |
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23-Sep |
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Dependency networks |
Gene network inference |
ppt1 pdf1 ppt2 pdf2 |
(1) Module networks (2) GENIE3 |
Prof. Roy |
| 4 |
28-Sep |
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Incorporating priors in Bayesian networks |
Integrative network inference |
ppt pdf |
(1) Werhli et al (2) Cancer signaling and DBN |
Prof. Roy |
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30-Sep |
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Incorporating priors in Dependency networks |
Integrative network inference |
ppt pdf |
(1) Inferelator (2) (optional) iRafNet |
Prof. Roy |
| 5 |
5-Oct |
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Network inference with single cell data |
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ppt pdf |
(1) PIDC; (2)SCENIC |
Prof. Roy |
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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 |
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I-O Hidden Markov Models |
Integrating TF-DNA interactions with time-series expression |
pptx pdf notes |
DREM |
Prof. Gitter |
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14-Oct |
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I-O Hidden Markov Models |
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Prof. Gitter |
| 7 |
19-Oct |
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Multi-task learning & GGMs |
Tissue-specific networks |
pptx pdf |
GNAT |
Prof. Gitter |
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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 |
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Graph neural networks 1 |
Protein-protein and protein-ligand interactions |
pptx pdf |
(1) Distill intros (2) Wu et al |
Prof. Gitter |
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28-Oct |
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Graph neural networks 2 |
Drug discovery |
pptx pdf |
|
Prof. Gitter |
| 9 |
2-Nov |
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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 |
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Spectral and Louvain clustering |
Finding modules in networks |
pptx pdf |
(1) Louvain clustering (2) Module detection challenge |
Prof. Roy |
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11-Nov |
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Dynamic network modules |
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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 |
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18-Nov |
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Matrix factorization based alignment |
Alignment of Protein-protein interaction networks |
pptx pdf |
FUSE |
Prof. Roy |
| 12 |
23-Nov |
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Graph alignment for single cell datasets |
Integrating scOmics data |
pptx pdf |
(1) SCANORAMA (2) LIGER |
Prof. Roy |
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25-Nov |
Thanksgiving |
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| 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 |
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2-Dec |
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Graph diffusion |
Interpreting cancer mutations |
pptx pdf |
HotNet |
Prof Gitter |
| 14 |
7-Dec |
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Steiner forest/integer programs |
Data integration |
pptx pdf |
(1) Omics Integrator (2) ILP |
Prof. Gitter |
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9-Dec |
Projects |
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| 15 |
14-Dec |
Projects |
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