Results for “molecular-generation”

Applies physical principles to model biological systems, including protein folding, membrane transport, molecular forces, and neural signaling.

Build and train graph neural networks for drug discovery, protein modeling, and molecular science using PyTorch-native tools.

Explains cellular structures, membrane transport, energetics, signaling, and division, connecting molecular events to organismal function.

Run and analyze molecular dynamics simulations with OpenMM and MDAnalysis. Set up protein/small molecule systems, define force fields, run energy minimization and production MD, analyze trajectories (RMSD, RMSF, contact maps, free energy surfaces).

Explains cell structure, organelles, signaling pathways, and cell cycle regulation for biology study and research.

Formulate testable hypotheses from observations, design experiments, and generate predictions using a structured scientific method framework.

Orchestrates a complete bulk RNA-seq differential-expression study from raw FASTQ reads through QC, alignment, quantification, differential expression, pathway enrichment, and publication figures.