Identifying protein function and functional links based on large-scale co-occurrence patterns.

ABSTRACT:

Objective

The vast majority of known proteins have not been experimentally tested even at the level of measuring their expression, and the function of many proteins remains unknown. In order to decipher protein function and examine functional associations, we developed "Cliquely", a software tool based on the exploration of co-occurrence patterns.

Computational model

Using a set of more than 23 million proteins divided into 404,947 orthologous clusters, we explored the co-occurrence graph of 4,742 fully sequenced genomes from the three domains of life. Edge weights in this graph represent co-occurrence probabilities. We use the Bron-Kerbosch algorithm to detect maximal cliques in this graph, fully-connected subgraphs that represent meaningful biological networks from differe

SUBMITTER: Pasternak Z 

PROVIDER: S-EPMC8893610 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature