GigaScienceBioinformaticsPeer-reviewed journal article
Contrast Subgraphs Allow Comparing Homogeneous and Heterogeneous Networks Derived from Omics Data
Tommaso LancianoiD, Aurora SavinoiD, Francesca Porcu, Davide CittaroiD, Francesco BonchiiD, Paolo ProveroiD
- Citations
- 9
- FWCI
- 0.73
- Field percentile
- top 35%
Abstract
Biological networks are often used to describe the relationships between relevant entities, in particular genes and proteins, and are a powerful tool for functional genomics. Many important biological problems can be investigated by comparing biological networks between different conditions, or networks obtained with different techniques. We show that contrast subgraphs, a recently introduced technique to identify the most important structural differences between two networks, provide a versatile tool for comparing gene and protein networks of diverse origin. We show in three concrete examples how contrast subgraphs can provide new insight in functional genomics by extracting the gene/protein modules whose connectivity is most altered between two conditions or experimental techniques.
- assay: protein sequence
- assay: protein structure
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: cell-cell communication
- approach: contrastive learning
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