Codes for software programs and mathematical models developed by our research.

Mathematical models for biological oscillators

  • 24h_model2019
    A systems pharmacological model for mammalian circadian clock of monkeys used to simulate the effect of the circadian clock modulator (Mathematica). See Kim et al., Systems approach reveals photosensitivity and PER2 level as determinants of clock‐modulator efficacy, Mol Syst Biol (2019) for details.
  • Phosphoswitch_Clock
    Mathematical models for mammalian circadian clock with the phosphoswitch (Mathematica). See Zhou, Kim et al, Mol Cell (2015) and Narasimamurthy R et al, PNAS (2018) for details.
  • Systems_pharmacology
    A systems pharmacology model for mammalian circadian clock of mice (Mathematica). See Kim JK, et al, Validating Chronic Pharmacological Manipulation of Circadian Rhythms, CPT:Pharmacometrics & Systems Pharmacology (2013) for details.
  • Kim-Forger model
    The detailed mathematical model for mammalian circadian clock (Mathematica, Matlab and XPPAUT). See Kim JK and Forger DB, A Mechanism for Robust Circadian Timekeeping via stoichiometric balance, Mol Syst Biol (2012) for details.
  • PER_p53
    A mathematical model describing molecular interactions between PER and p53 (Mathematica). See Gotoh and Kim et al., Model-driven experimental approach reveals the complex regulatory distribution of p53 by the circadian factor Period 2, PNAS (2016) for details.
  • dual_strain_synthetic_oscillator
    Mathematical model of dual strain synthetic oscillator (Mathematica). See Ye and Kim et al., Emergent genetic oscillations in a synthetic microbial consortium, Science (2015) for details.

Bayesian inference algorithms

  • Delay
    Bayesian inference algorithm (R code) that estimates reaction rates and delay distribution of Birth-Death process with time delay. See Choi et al., Bayesian inference of distributed time delay in transcriptional and translational regulation, Bioinformatics (2019) for details
    R package that performs the Bayesian inference for enzyme kinetics with the total quasi-steady-state approximation model. See Choi et al., Beyond the Michaelis-Menten equation: Accurate and efficient estimation of enzyme kinetic parameters, Scientific Reports (2017) for details.

Stochastic analysis

  • Feedme
    Matlab code for the calculation of exact moments of biochemical reaction networks with feed-forward structures. See Kim and Sontag, Reduction of Multiscale Stochastic Biochemical Reaction Networks using Exact Moment Derivation, PLoS Com Biol (2017) for details.

Diagnosis for sleep disorders

  • OSA-phenotyping
    A computational package (Python) that can phenotype obstructive sleep apnea (OSA) patients based on their polysomnography (PSG) data. See Ma et al., Combined unsupervised‑supervised machine learning for phenotyping complex diseases with its application to obstructive sleep apnea, Scientific Reports (2021) for details.