Paralog Explorer: A resource for mining information about paralogs in common research organisms

Paralogs are genes which arose via gene duplication, and when such paralogs retain overlapping or redundant function, this poses a challenge to functional genetics research. Recent technological advance-ments have made it possible to systematically probe gene function for redundant genes using dual or multiplex gene perturbation, and there is a need for a simple bioinformatic tool to identify putative par-alogs of a gene(s) of interest. We have developed Paralog Explorer (https://www.flyrnai.org/tools/par-alogs/), an online resource that allows researchers to quickly and accurately identify candidate paralogous genes in the genomes of the model organisms D. melanogaster, C. elegans, D. rerio, M. musculus, and H. sapiens. Paralog Explorer deploys an effective between-species ortholog prediction software, DIOPT, to analyze within-species paralogs. Paralog Explorer allows users to identify candidate paralogs, and to navigate relevant databases regarding gene co-expression, protein-protein and genetic interac-tion, as well as gene ontology and phenotype annotations. Altogether, this tool extends the value of cur-rent ortholog prediction resources by providing sophisticated features useful for identification and study of paralogous genes.(c) 2022 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY license (http://creativecommons. org/licenses/by/4.0/).

Automated summary

Paralogs are genes that arise through gene duplication and pose a challenge to functional genetics research when they retain overlapping or redundant function. We have developed Paralog Explorer, an online resource that enables researchers to identify candidate paralogous genes in model organisms' genomes and provides access to relevant databases for gene co-expression, protein-protein and genetic interactions, as well as gene ontology and phenotype annotations. This tool expands the capabilities of current ortholog prediction resources for the identification and study of paralogous genes.