Fig. 1: Overview of the EvoWeaver algorithm and benchmarking.
From: EvoWeaver: large-scale prediction of gene functional associations from coevolutionary signals
a Phylogenetic trees from groups of orthologous genes serve as the primary input to EvoWeaver. Four categories of coevolutionary signal are quantified for each pair of genes. These signals are combined in an ensemble classifier to predict functional relationships between gene pairs. EvoWeaver provides as output its 12 predictions for signals of coevolution, and can optionally provide an ensemble prediction using built-in pretrained models. b Functional associations often result in correlated gain/loss patterns on a reference phylogenetic tree (e.g., a species tree). EvoWeaver assesses the presence/absence patterns, correlation between gain/loss events, and distance between gain/loss events as signals of coevolution. c Similarity in phylogenetic structure is another indicator of coevolution between genes. EvoWeaver computes topological distance as well as correlation in patristic distances following dimensionality reduction using random projection. d Functionally associated genes sometimes cluster on the genome due to co-regulation or horizontal gene transfer. EvoWeaver derives signals from the conservation in gene orientation and the distance between gene pairs. e Functional associations sometimes cause concerted changes in sequences that are interrogated by EvoWeaver. EvoWeaver can analyze nucleotide sequences or amino acid sequences, though nucleotide sequences are pictured here. f Proteins involved in the same complex are functionally associated and can be identified through signals of coevolution. The goal of the Complexes benchmark is to distinguish orthology groups in the same complex (i.e., positives) from those in different complexes (i.e., negatives). g Functional associations between proteins that are adjacent in the same module are stronger than those between different modules. The goal of the Modules benchmark is to distinguish adjacent proteins in the same module from independent modules. Created in BioRender. Lakshman, A. (2025) https://BioRender.com/m73q207.
