GitHub topics: graph-distance
dubssieg/rs-pancat-compare
Compares pangenome graphs by calculating the segmentation distance between two GFA (Graphical Fragment Assembly) files.
Language: Rust - Size: 2.79 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 9 - Forks: 0
YertleTurtleGit/graph-pca
Performs PCA with optional graph distance for neighborhood composition.
Language: Rust - Size: 3.03 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0
pingkoc/cutnorm
This package computes the approximations to the cutnorm using some of the techniques detailed by Alon and Noar [ALON2004] and a fast optimization algorithm by Wen and Yin [WEN2013].
Language: Python - Size: 736 KB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 1 - Forks: 1
priba/siamese_ged
Learning Graph Distances with Message PassingNeural Networks
Language: Python - Size: 164 MB - Last synced at: 4 months ago - Pushed at: 12 months ago - Stars: 13 - Forks: 12
AntoinePassemiers/GDE-GaussFold
Lightning-Fast Template-free Protein Folding based on Predicted Residue Contacts and Secondary Structure
Language: Python - Size: 592 KB - Last synced at: over 1 year ago - Pushed at: almost 6 years ago - Stars: 2 - Forks: 0
50-Cent/ElasticPath2Path
Morphological categorization of neurons in order to explore their functional features has drawn significant attention over past few decades. The enormous complexity in the structure of neurons poses a real challenge in the identification and analysis of similar and dissimilar neuronal cells. Existing methodologies often carry out strutural and geometrical simplifications, which substantially changes the morphological statistics. Using digitally-reconstructed neurons, we extend the work of Path2Path as ElasticP2P, which seamlessly integrates the graph-theoretic and differential-geometric frameworks. By decomposing a neuron into a set of paths, we derive graph metrics, which are path concurrence and path hierarchy. Next, we model each path as an elastic string to compute the geodesic distance between the paths of a pair of neurons. Later, we formulate the problem of finding the distance between two neurons as a path assignment problem with a cost function combining the graph metrics and the geodesic deformation of paths.
Language: Matlab - Size: 19.5 KB - Last synced at: over 1 year ago - Pushed at: over 7 years ago - Stars: 1 - Forks: 0
gasteigerjo/gtn
Graph transport network (GTN), as proposed in "Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More" (ICML 2021)
Language: Jupyter Notebook - Size: 7.84 MB - Last synced at: over 2 years ago - Pushed at: over 3 years ago - Stars: 14 - Forks: 3
msarrias/graph-distance-for-complex-networks
reproducing Shimada et al. 2016 "Graph distance for complex networks" paper
Language: Jupyter Notebook - Size: 3.24 MB - Last synced at: over 2 years ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0
