Machine Learning Identifies Murine Cardiac Development Genes
Researchers published February 10, 2026, present a supervised machine learning classifier that identifies mouse genes involved in cardiac development and prioritises candidates for human congenital heart disease (CHD). The model achieved 81% cross-validation accuracy and produced genome-wide predictions for all protein-coding mouse genes, showing high overlap with known human CHD genes. These predictions can aid gene prioritisation in patient sequencing and accelerate genetic diagnosis.
Scoring Rationale
Peer-reviewed, actionable ML predictions with validated overlaps to human CHD genes; limited novelty versus prior methods.
Practice interview problems based on real data
1,500+ SQL & Python problems across 15 industry datasets — the exact type of data you work with.
Try 250 free problems
