Nima P. Saadat

Helixer, a hybrid convolutional/bLSTM network with a hidden Markov model post-processor, predicts eukaryotic primary gene models from DNA alone, outscoring GenemarkES and AUGUSTUS on most species.

The paper uses a mathematical model to study how external conditions affect control over carbon fixation in photosynthesis.

The paper introduces moped, a Python package for reproducible metabolic model construction, curation, and analysis, supporting both genome-based reconstruction and SBML import.

The paper develops a merged theoretical model to analyze how energy and redox supply in photosynthesis matches carbon fixation demand, showing the necessity of a stand-by mode for efficient carbon fixation.

The paper introduces modelbase, a Python package for building and analyzing dynamic mathematical models of biological systems, with features for ODE assembly and isotope-specific modeling.