Researchers improve blood tests’ ability to detect and monitor cancer
The advance makes it easier to detect circulating tumor DNA in blood samples, which could enable earlier cancer diagnosis and help guide treatment.
The advance makes it easier to detect circulating tumor DNA in blood samples, which could enable earlier cancer diagnosis and help guide treatment.
MIT researchers can now track a cell’s RNA expression to investigate long-term processes like cancer progression or embryonic development.
By analyzing bacterial data, researchers have discovered thousands of rare new CRISPR systems that have a range of functions and could enable gene editing, diagnostics, and more.
MIT study suggests 3D folding of the genome is key to cells’ ability to store and pass on “memories” of which genes they should express.
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.