AI to help researchers see the bigger picture in cell biology
By providing holistic information on a cell, an AI-driven method could help scientists better understand disease mechanisms and plan experiments.
Broad Institute
3 Questions: Using AI to accelerate the discovery and design of therapeutic drugs
Professor James Collins discusses how collaboration has been central to his research into combining computational predictions with new experimental platforms.
Read MoreMIT scientists investigate memorization risk in the age of clinical AI
New research demonstrates how AI models can be tested to ensure they don’t cause harm by revealing anonymized patient health data.
Read MoreNew AI system could accelerate clinical research
By enabling rapid annotation of areas of interest in medical images, the tool can help scientists study new treatments or map disease progression.
Read More3 Questions: On biology and medicine’s “data revolution”
Professor Caroline Uhler discusses her work at the Schmidt Center, thorny problems in math, and the ongoing quest to understand some of the most complex interactions in biology.
Read MoreHow to more efficiently study complex treatment interactions
A new approach for testing multiple treatment combinations at once could help scientists develop drugs for cancer or genetic disorders.
Read MoreCellLENS reveals hidden patterns in cell behavior within tissues, offering deeper insights into cell heterogeneity — vital for advancing cancer immunotherapy.
Read MoreRationale engineering generates a compact new tool for gene therapy
Researchers redesign a compact RNA-guided enzyme from bacteria, making it an efficient editor of human DNA.
Read MoreWith AI, researchers predict the location of virtually any protein within a human cell
Trained with a joint understanding of protein and cell behavior, the model could help with diagnosing disease and developing new drugs.
Read MoreThe programmable proteins are compact, modular, and can be directed to modify DNA in human cells.
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