Stanford scientists have developed Plate-C, a high-throughput screening platform that captures genome-wide 3D chromatin architecture as a comprehensive cellular phenotype.
Stanford researchers have developed a novel technology called FLASH (Functional Assigning Sequence Homing) that predicts phenotypes directly from raw sequencing data, bypassing assembly and alignment, while revealing the biological features driving those predictions.
Researchers in Professor Justin Sonnenburg's laboratory have developed genetic tools for manipulating Bacteroides, a prominent genus of gut bacteria, for imaging, diagnostics, and therapeutic drug delivery.
Stanford researchers have developed MONTAGE, a powerful computational framework designed to identify groups of cells, called spatial communities, and map how these groups change across biological functions linked to cancer progression.
Stanford researchers have developed an innovative method for efficiently generating robust lymphatic endothelial cells (iLECs) from human induced pluripotent stem cells (hiPSCs) through transcription factor-based protocols.
Stanford researchers have developed a system that assesses altered mental states in both human and animal subjects using neural biomarkers, allowing for repeatable cross-species studies of potential treatments for psychiatric and neurological disorders.
Stanford researchers have developed Screen-GPT, an AI-powered multi-agent platform that automates CRISPR genetic screening by integrating diverse biological data to design libraries and prioritize targets through transparent, explainable, and scalable workflows.
Stanford scientists have developed innovative methods for safely collecting, preserving, imaging, and molecularly profiling human brain tissue that remains on explanted intracranial electrodes used in neurosurgical procedures.
Non-small-cell lung cancer (NSCLC) accounts for approximately 85% of all lung cancer cases, making it the leading cause of cancer-related deaths globally. Post-surgical recurrence and treatment resistance are the main causes of cancer-related mortality.
Stanford researchers have developed a more sensitive and accurate pathogenic infection diagnosis method using intact genetically modified pathogens. Pathogen infection clinical diagnosis requires direct pathogen detection or the detection of pathogen specific antibodies.
Stanford researchers have developed a fast and flexible platform for building human brain organoids that mimic the complexity of the brain's cellular makeup. This breakthrough enables faster research and better disease modeling for neurological conditions.