Many Needles in a Haystack: Active Hit Discovery for Perturbation Experiments

• URL: http://arxiv.org/abs/2605.10196v1
• Date: Mon, 11 May 2026 08:45:19 GMT
• Title: Many Needles in a Haystack: Active Hit Discovery for Perturbation Experiments
• Abstract summary: High- throughput gene perturbation experiments can test several genetic interventions in parallel, yet experimental budgets remain limited.<n>A central goal is hit discovery: identifying as many perturbations as possible whose effect exceeds a predefined threshold.<n>We propose a principled alternative but target a single global optimum, over-exploiting dominant modes while neglecting other high-value regions.
• Score: 19.510272466719044
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: High-throughput gene perturbation experiments can test several genetic interventions in parallel, yet experimental budgets remain limited. A central goal is hit discovery: identifying as many perturbations as possible whose phenotypic effect exceeds a predefined threshold. Pure exploration strategies are statistically inefficient, wasting budget on low-value regions. Bayesian optimization methods offer a principled alternative but target a single global optimum, over-exploiting dominant modes while neglecting other high-value regions. We formalize hit discovery as a sequential experimental design problem and propose Probability-of-Hit, an acquisition function that directly targets threshold exceedance by ranking candidates according to their posterior probability of being a hit. We prove asymptotic optimality of this approach and demonstrate strong empirical performance on both synthetic benchmarks and real biological immunology datasets, including up to 6.4% improvement over baselines on the Schmidt IL-2 dataset.

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