Waisman Center
Advancing knowledge of human development, developmental disabilities, and neurodegenerative diseases.

ECMarker: interpretable machine learning model identifies gene expression biomarkers predicting clinical outcomes and reveals molecular mechanisms of human disease in early stages

Wang, PhD, D. ECMarker: Interpretable Machine Learning Model Identifies Gene Expression Biomarkers Predicting Clinical Outcomes and Reveals Molecular Mechanisms of Human Disease in Early Stages.
Jin, T., Nguyen, N. D., Talos, F., & Wang, D. (2021). ECMarker: interpretable machine learning model identifies gene expression biomarkers predicting clinical outcomes and reveals molecular mechanisms of human disease in early stages. Bioinformatics (Oxford, England), 37(8), 1115–1124. https://doi.org/10.1093/bioinformatics/btaa935