Ming‐Jung Liu

TISCalling: Leveraging Machine Learning to Identify Translational Initiation Sites in Plants and Viruses

TISCalling identifies and ranks translational initiation sites in plants and viruses using machine learning and statistical analysis, providing prediction scores and web tools for visualization.

Visualization and Prediction of in vivo Phosphate Dynamics via Auto-Glowing Plant Sensors

This paper develops a biosensor to visualize and predict phosphorus deficiency in plants using bioluminescence and deep learning.

PREDICT: Advancing Accurate Gene Expression Prediction and Motif Identification in Plant Stress Responses

The paper develops a k-mer pipeline to predict gene expression and identify transcription factor binding motifs in plant stress responses, introducing the PREDICT database.

Modeling alternative translation initiation sites in plants reveals evolutionarily conserved cis-regulatory codes in eukaryotes

The paper develops a model to predict alternative translation initiation sites in plants, revealing conserved cis-regulatory codes across eukaryotes and viruses.