Making genetic prediction models more inclusive
MIT computer scientists developed a way to calculate polygenic scores that makes them more accurate for people across diverse ancestries.
MIT computer scientists developed a way to calculate polygenic scores that makes them more accurate for people across diverse ancestries.
New research finds RNA-guided enzymes called Fanzors are widespread among eukaryotic organisms.
By analyzing epigenomic and gene expression changes that occur in Alzheimer’s disease, researchers identify cellular pathways that could become new drug targets.
The findings could help doctors identify cancer patients who would benefit the most from drugs called checkpoint blockade inhibitors.
Researchers compared a pair of superficially similar motor neurons in fruit flies to examine how their differing use of the same genome produced distinctions in form and function.
MIT engineers developed a new way to create these arrays, by scaffolding quantum rods onto patterned DNA.
In addition to turning on genes involved in cell defense, the STING protein also acts as an ion channel, allowing it to control a wide variety of immune responses.
MIT researchers find timing and dosage of DNA-damaging drugs are key to whether a cancer cell dies or enters senescence.
Whitehead Institute researchers find many transcription factors bind RNA, which fine-tunes their regulation of gene expression, suggesting new therapeutic opportunities.
“FrameDiff” is a computational tool that uses generative AI to craft new protein structures, with the aim of accelerating drug development and improving gene therapy.
A new approach for identifying significant differences in gene use between closely-related species provides insights into human evolution.
The first RNA-guided DNA-cutting enzyme found in eukaryotes, Fanzor could one day be harnessed to edit DNA more precisely than CRISPR/Cas systems.
MIT researchers characterize gene expression patterns for 22,500 brain vascular cells across 428 donors, revealing insights for Alzheimer’s onset and potential treatments.
With the new method, scientists can explore many cancer mutations whose roles are unknown, helping them develop new drugs that target those mutations.
MIT engineers’ new technique analyzes the 3D organization of the genome at a resolution 100 times higher than before.