CITATION.cff

cff-version: 1.2.0
message: >
  If you use KinOpt in your research, please cite it using the
  metadata in this file.
title: "KinOpt: Optimization-based estimation of cumulative kinase effects on substrate phosphorylation, including the effects of kinase autophosphorylation on its own activity."
authors:
  - family-names: Mishra
    given-names: Abhinav
    orcid: "https://orcid.org/0009-0005-3179-7408"
repository-code: "https://github.com/bibymaths/KinOpt"
url: "https://bibymaths.github.io/KinOpt"
license: BSD-3-Clause
version: "0.9.0"
keywords:
  - phosphorylation
  - kinetics
  - optimization
  - systems biology
  - time-series
  - Python
type: software
abstract: >
  KinOpt is a modular framework designed for the analysis and optimization
  of gene–phosphorylation time-series data. It integrates several specialized
  submodules that cater to different optimization strategies and post-processing
  analyses. Whether you need a global evolutionary approach, a local constrained
  optimization, or a Julia-based Powell optimization routine, it offers the
  tools to process your experimental data and generate in-depth reports on model
  performance.