⚙️Running Graph Algorithms

How to run graph algorithms to identify paths and prioritize data points.

Path Finding

Shortest Path

Shortest path will compute the shortest path between two nodes.

Add a few objects to your view. select Algorithm > Path Finding > Shortest path

Using the dialog specify the following

• Start Node

  • Any 1 of your objects that are currently in view

• End Node

  • Any 1 of your objects that are currently in view

• Min Hops

  • The minimum amount of hops between the start and end node

• Max Hops

  • The maximum amount of hopes between the start and end node

Submitting the dialog will populate the results in a new tab

Learn more about A* Star Here https://neo4j.com/docs/graph-data-science/current/algorithms/astar/

All shortest Paths

All shortest paths will return a list of all shortest paths between two nodes.

Add a few objects to your view. select Algorithm > Path Finding > All shortest paths

Using the dialog specify the following

• Start Node

  • Any 1 of your objects that are currently in view

• End Node

  • Any 1 of your objects that are currently in view

• Min Hops

  • The minimum amount of hops between the start and end node

• Max Hops

  • The maximum amount of hopes between the start and end node

Submitting the dialog will populate the results in a new tab. Select a path from the table to view the nodes and relationships.

Centrality

Page Rank

The PageRank algorithm measures the importance of each node within the graph, based on the number incoming relationships and the importance of the corresponding source nodes. This assumes that a node is only as important as the nodes that link to it.

To use Page Rank, configure a network within your nebula

Select Algorithm > Centrality > Page Rank

Parameters available for configuration

• Damping factor

  • Determines the likelihood that a user will traverse from one node (e.g., gene, protein) to another, influencing the significance assigned to connections between biological entities.

  • By default this is set to 0.8.

• Precision

  • Refers to the degree of accuracy in determining the significance and relevance of biological entities within the network based on their connectivity and importance in biological processes.

  • By default this is set to 0.000001.

• Iterations

  • Denotes the number of sequential computational steps taken to calculate the importance of biological entities based on their connections within the network, potentially affecting the accuracy of the ranking process.

  • By default this is set to 200

The results will populate in a table below the tabs. The score associated with each node reflects the relative importance of biological entities (such as genes or proteins) based on their interconnectedness and influence within biological processes.

Learn more about Page Rank here

• Original Google Paper http://infolab.stanford.edu/~backrub/google.html