Yuanhao Qu

AutoScreen: AI Co-Scientist System for Target Discovery in Functional Genomics

AutoScreen improves gene prioritization in functional genomics by integrating AI agents for pre-screen design and post-screen analysis, achieving higher hit recovery and precision than existing methods.

BiomniBench: Process-level Evaluation of LLM Agents for Real-world Biomedical Research

BiomniBench evaluates LLM agents' research processes in biomedical tasks using expert rubrics, revealing performance gaps in method selection and reasoning.

Disease-Linked Regulatory DNA Variants and Homeostatic Transcription Factors in Epidermis

The paper identifies disease-linked regulatory DNA variants and their impact on epidermal homeostasis by analyzing SNVs, TF binding, and gene dysregulation in polygenic skin diseases.

BioLab: End-to-End Autonomous Life Sciences Research with Multi-Agents System Integrating Biological Foundation Models

BioLab uses a multi-agent system with foundation models to autonomously design and validate antibodies, achieving superior performance compared to existing methods.

CRISPR-GPT for Agentic Automation of Gene Editing Experiments

CRISPR-GPT automates CRISPR-based gene-editing design and analysis by integrating LLMs with domain expertise, demonstrating effectiveness in gene knockout and activation experiments.

Genome-Bench: A Scientific Reasoning Benchmark from Real-World Expert Discussions

The paper introduces Genome-Bench, a benchmark created from scientific forum discussions, and presents a pipeline to convert these into reinforcement learning-friendly multiple-choice questions.

Biomni: A General-Purpose Biomedical AI Agent

An LLM agent with a literature-mined environment of 150 tools, 105 packages and 59 databases plans in code, matching reported human accuracy on database and sequence question answering.

Autonomous AI Agents Discover Aging Interventions from Millions of Molecular Profiles

The paper reanalyzes millions of molecular profiles to identify aging interventions using AI agents, finding over 500 interventions that reduce biological age and revealing patterns in aging modulation.

CRISPRa screening with real world evidence identifies potassium channels as neuronal entry factors and druggable targets for SARS-CoV-2

The paper uses CRISPRa screening and real-world data to identify KCNA6 as a neuronal entry factor for SARS-CoV-2 and shows dalfampridine can suppress viral entry.