AI-Driven Multi-Omics Interpretation for Target and Biomarker Discovery

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About Our Platform

Integrative Foundation Models for Translational Genomics

OmicxIQ.Ai is an AI-powered platform that unifies genomic, proteomic, and transcriptomic foundation models to identify clinically actionable drug targets and biomarkers. By layering insights across omics, OmicxIQ.Ai provides a comprehensive understanding of variant pathogenicity and disease relevance, streamlining the path from data to therapeutic insight.

Why Use OmicxIQ.Ai?

From Variant Classification to Pathway-Level Insight

Traditional variant interpretation often lacks the biological context needed for therapeutic translation. OmicxIQ.Ai bridges this gap by integrating multi-omic models to not only classify genetic variants but also assess their downstream impact on protein function, gene expression, and disease-associated pathways—enabling high-confidence target discovery and precision biomarker identification.

HOW IT WORKS

Multi-Layered AI Models for Variant-
to-Mechanism Mapping

OmicxIQ.Ai begins with EVO2, a genomic foundation model that classifies variants as pathogenic or benign. These predictions are refined using AlphaMissense, a proteomic model that evaluates the structural and functional consequences of missense mutations. Transcriptomic models then assess whether affected genes are dysregulated in disease contexts. Finally, variants are mapped to biological pathways using integrated genetic and protein interaction networks to uncover mechanistic insights and therapeutic opportunities.

Key Features & Capabilities

AI-Augmented Target and Biomarker Discovery at Scale

Multi-Omic Foundation Model Integration

Combines genomics, proteomics, and transcriptomics for layered variant interpretation.

Variant Pathogenicity Prediction

Uses EVO2 to assess likelihood of genetic variants being disease-causing.

Functional Consequence Analysis

Employs AlphaMissense to model structural and functional impact on proteins.

Transcriptomic Dysregulation Profiling

Evaluates gene expression changes in disease-relevant tissues.

Pathway-Level Insight

Maps variants to biological networks to identify mechanisms and intervention points.

End-to-End Interpretation Pipeline

Translates raw variant data into druggable targets and clinically relevant biomarkers.

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