AI工具精准显示基因开启和关闭的时间

Summary：

• Yale researchers developed chronODE, an AI - powered tool. It models gene on - off during brain development by combining math, machine learning and genomic data to find "switching points" of gene maximum activity.
• Most genes have predictable activation patterns and can be classified. This may help doctors time gene therapies or drug interventions.
• chronODE uses math and AI for gene - chromatin change modeling. Switching points are for intervention, and gene patterns are predictable during development.

Key Facts：

• chronODE Tool: Combines math and AI for real - time gene activation and chromatin change modeling.
• Switching Points: Critical for intervention in disease progression.
• Gene Patterns: Predictable during development.

Yale team's chronODE can pinpoint gene on - off during brain development. It uses math and machine learning to model gene - chromatin patterns over time.

Most genes follow predictable patterns based on cell role and speed to maximum influence.

For the study, researchers used a logistic equation to measure mouse brain gene on - off. Genes have simple activation patterns and can be grouped into subtypes.

An AI model was developed to predict gene expression based on chromatin changes.

In treating genetic disease, the equation can show the "switching point".

The method is named "chronODE", merging time concept with ODEs.

Authors include Borsari, Frank and others.