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Graph Neural Networks for Biological Network Modeling Training | GCN/GAT/GraphSAGE, Heterogeneous Graphs, Link Prediction

NTHRYS >> Services >> Academic Services >> Training Programs >> Bioinformatics Training >> AI/ML, Data Science, Pipelines & Cloud >> Graph Neural Networks for Biological Network Modeling Training | GCN/GAT/GraphSAGE, Heterogeneous Graphs, Link Prediction

Graph Neural Networks for Biological Network Modeling — Hands-on

Learn to represent complex biological systems as graphs and train state-of-the-art Graph Neural Networks (GNNs) for discovery. You will implement end-to-end pipelines for node/edge/graph tasks over PPIs, gene regulatory networks, knowledge graphs, pathways, and molecular graphs—complete with scalable sampling, hyperparameter tuning, and rigorous evaluation.

Graph Neural Networks for Biological Network Modeling
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Session 1
Fee: Rs 12,000
Bio Graphs: Data & Tasks
  • Graph basics & biological schemas
  • PPIs / GRNs / pathways drug–target / disease–gene molecular graphs
  • Tasks & splits for graphs
  • node classification link prediction graph classification
  • Toolchain & data loaders
  • PyTorch Geometric DGL OGB splits
Session 2
Fee: Rs 16,400
Core GNN Architectures
  • Message passing & inductive bias
  • GCN / GAT GraphSAGE GIN
  • Molecular & geometric extensions
  • edge/bond features radius/3D coords equivariance
  • Regularization & training
  • dropout/weight decay batch/graph norm early stopping
Session 3
Fee: Rs 20,800
Heterogeneous, Scaling & Evaluation
  • Heterogeneous & knowledge graphs
  • metapaths / HAN relation-specific conv KG embeddings
  • Scaling & sampling
  • neighbor sampling GraphSAINT/Cluster-GCN mini-batch inference
  • Evaluation & interpretability
  • AUC/AP/ROC-PR temporal splits GNNExplainer / subgraphs
Session 4
Fee: Rs 26,000
Mini Capstone: Link Prediction
  • Build a link prediction model for PPIs or drug–target
  • Theory + Practical
  • Explain model decisions & report
  • subgraph rationales counterfactual edges model card
  • Deliverables: code, metrics & brief
  • notebook/script ROC/PR plots PDF/HTML


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