Simple Models and Exact Algorithms for Computing Network Modules
summary
Presents a sparse pairwise alignment that restricts each node to a candidate set and encodes edge conservation as a quadratic objective, solved by Lagrangian relaxation and variable splitting; on STRING networks with ~150,000 edges the method (Natalie) reaches near-optimal lower bounds within 1–2% and beats a recent tool (elegua) under a 10-minute CPU limit. Also frames active modules as the maximum-weight connected subgraph, reduces it to prize-collecting Steiner, ships an ILP solver and a Cytoscape plugin, and pinpoints an HGF–MET–HCF axis validated by expression follow-up.
AI-written summary · about
chapters (9)
- 0:00Intro
- 0:30Network biology
- 1:45Subnetwork modules
- 3:35Pairwise restricted global network alignment
- 5:50Quadratic assignment
- 7:45Integer programming model
- 15:20How to model the signal?
- 19:26Results: Herpesvirus project
- 23:21Why simple models ? Systems
related talks
01h 06mIntroduction to Biological Network Analysis III: Identifying Network Modules
52mNew Algorithms For The Graph Alignment Problem
49mIntroduction to Biological Network Analysis IV: Network Alignment and Querying
38mThe NetworkL python package
29mSampling Algorithms for Combinatorial Pure Exploration
01h 04mNonparametric Bayesian Methods: Models, Algorithms, and Applications IV
35mLocal Statistics, Semidefinite Programming, and Community Detection II
55mDistribution-Free Models of Social and Information Networks
