ODin (Orthology Data driven Interaction) Predictor: A Client‑Side Web Application for Unveiling Biological Connections Through Orthology from Alliance of Genome Resources

Deciphering the complex landscape of gene interactions is essential for understanding biological systems and unraveling the mechanisms underlying disease. While experimental approaches to mapping these interactions are often labor-intensive and costly, computational strategies-particularly those that exploit evolutionary conservation through orthology-provide a powerful and scalable alternative. We present a novel client-side web application that infers gene interactions by leveraging comprehensive orthology and experimentally validated protein-protein or genetic interactions from the Alliance of Genome Resources. This tool substantially broadens known interactomes, especially for underrepresented model organisms such as zebrafish and <i>Xenopus</i> with less studied interactions. Its client-side architecture ensures exceptional data privacy and instantaneous results, setting it apart from conventional server-based platforms. By integrating these predictions with structural evidence and biological context, researchers may gain more reliable biological insights, helping to support more efficient and precisely targeted scientific discovery.

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Publication Details

Journal
PubMed
Published
2025-10-31
DOI
https://doi.org/10.17912/micropub.biology.001923
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
0.00
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article

ODin (Orthology Data driven Interaction) Predictor: A Client‑Side Web Application for Unveiling Biological Connections Through Orthology from Alliance of Genome Resources

Jaehyoung Cho, Paul W Sternberg
PubMed
Bioinformatics and Genomic Networks
article

ODin (Orthology Data driven Interaction) Predictor: A Client‑Side Web Application for Unveiling Biological Connections Through Orthology from Alliance of Genome Resources

Jaehyoung Cho, Paul W Sternberg
article en

Abstract

Deciphering the complex landscape of gene interactions is essential for understanding biological systems and unraveling the mechanisms underlying disease. While experimental approaches to mapping these interactions are often labor-intensive and costly, computational strategies-particularly those that exploit evolutionary conservation through orthology-provide a powerful and scalable alternative. We present a novel client-side web application that infers gene interactions by leveraging comprehensive orthology and experimentally validated protein-protein or genetic interactions from the Alliance of Genome Resources. This tool substantially broadens known interactomes, especially for underrepresented model organisms such as zebrafish and <i>Xenopus</i> with less studied interactions. Its client-side architecture ensures exceptional data privacy and instantaneous results, setting it apart from conventional server-based platforms. By integrating these predictions with structural evidence and biological context, researchers may gain more reliable biological insights, helping to support more efficient and precisely targeted scientific discovery.

PubMedVol. 2026
Openalex Percentile: Top 32%
Bioinformatics and Genomic Networks
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