Skip to content

DaehwanKimLab/lcc

Repository files navigation

lcc - Life Compiler Collection

Required programs: Python3
Required Python packages: NumPy, TensorFlow
Required dataset formats: txt, tsv, csv

This repository contains a lcc, or Life Compiler Collection, which compiles a code for Function of Life of the LDP team. Function of Life is a mathematical function that describes cellular processes, using a series of matrix operations on GPU.

Setup

For the best experience, we recommend using Conda as a package, dependency and environment management system that is compatible with Windows, macOS, and Linux.

Setup Python Environment

conda env create -f environment.yml

conda activate lcc
conda deactivate

GPU Support

conda env create -f environment-gpu.yml

conda activate lcc-gpu
conda deactivate

GPU environment requires NVIDIA GPU Driver 450.x or higher

Program Design

###lcc.py lcc.py parse the genome using compiler database and generates a whole cell simulation code.

Input

  • Genome sequence file(s) (.fasta)

Output

  • cell.py: Whole cell simulation execution code, a.k.a. Function of Life
  • CompilerData save files (.npy)

###cell.py cell.py

# Instantiate all data components.
Cst = FConstant()
Env = FEnvironment()
Cel = FCellState()

# Instantiate all reaction components.
Exe = FRateGaugeModelOnly()
Bch = FBiochemicalReactionRateFunction()
Pol = FPolymerizationRateFunction()

# Instantiate cell process objects.
Replication = FReplication(Bch, Cel, Cst, Env, Exe, Pol)

# Generate a dictionary of cell process object names
Dict_CellProcesses = dict()
Dict_CellProcesses['Replication'] = Replication

# Instantiate simulation object.
Sim = FSimulation(Bch, Cel, Cst, Env, Exe, Pol, Dict_CellProcesses)
    
# Declare temporary parameters
Cel.Vol = tf.constant([7e-16])

# Run simulation.
Sim.Initialize()
Sim.Run()

Input

  • CompilerData save files (.npy)

Output

  • Molecule count readout