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New Agentic Framework ARGUS Improves Genomic Variant Interpretation

By PulseAugur Editorial · [1 sources] ·

Researchers have developed ARGUS, an agentic framework designed to improve the interpretation of single nucleotide variants (SNVs) in noncoding regulatory regions of the genome. Unlike standard large language models that often hallucinate or fabricate evidence, ARGUS employs a structured approach. It integrates deterministic biological computation with LLM-mediated reasoning, using a planner to select evidence sources and a verifier to interpret observations, thereby reducing uncertainty and improving the accuracy of functional interpretation for disease-associated variants. AI

IMPACT This framework offers a more reliable method for interpreting genomic data, potentially accelerating discoveries in personalized medicine by reducing LLM-induced errors.

RANK_REASON The cluster describes a new research framework for interpreting genomic variants, published as a scientific paper on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New Agentic Framework ARGUS Improves Genomic Variant Interpretation

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The cluster describes a new research framework for interpreting genomic variants, published as a scientific paper on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Pratik Dutta, Matthew B. Obusan, Max Chao, Rekha Sathian, Nimisha Papineni, Ramana V. Davuluri ·

    Unlocking the Regulatory Genome by ARGUS: An Evidence-Constrained Agentic Framework for Interpreting Single Nucleotide Variants

    arXiv:2610.12281v1 Announce Type: cross Abstract: Over 90% of disease-associated variants from genome-wide association studies fall in noncoding regulatory regions, yet their functional interpretation remains a central open problem in genomic medicine. Large language models promp…

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