GeneNet Toolbox

GeneNet Toolbox computes statistical significance of connectivity among seed-genes within biological networks to assess gene interactions and network structure.

Key Features:

• Connectivity Analysis: Uses seed randomization (comparing observed connections against random gene sets) and network permutation (shuffling network edges while preserving node degrees) to evaluate significance among seed-genes.
• Subnetwork Restriction: Allows restriction of analyses to specified subnetworks within the primary biological network.
• Extended Connectivity Analysis: Calculates connectivity from seed-genes to an additional set of genes of interest.
• Pre-analysis Algorithm Selection: Provides pre-analysis tools to assist selection of the most appropriate connectivity-analysis algorithm for given network data.
• Visualization Capabilities: Generates graphical representations of connections among seed-genes.
• Performance: Capable of processing networks with approximately 10 million edges on a standard desktop computer.
• MATLAB Implementation: Implemented as a MATLAB toolbox.

Scientific Applications:

• Systems Biology: Investigating network-level gene interactions and regulatory mechanisms in systems biology studies.
• Genomics: Interpreting gene connectivity in genomics datasets to inform gene function and regulatory relationships.
• Personalized Medicine: Identifying candidate genes or pathways relevant to therapeutic targeting in personalized medicine contexts.

Methodology:

Calculates connectivity significance via seed randomization (comparison to random gene sets) and network permutation (edge shuffling while preserving node degrees); supports restriction to subnetworks and extension of connectivity calculations to additional gene sets; includes pre-analysis tools to evaluate algorithm suitability.