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longxf21 committed Oct 14, 2024
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24 changes: 24 additions & 0 deletions .github/workflows/draft-pdf.yml
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name: Draft PDF
on: [push]

jobs:
paper:
runs-on: ubuntu-latest
name: Paper Draft
steps:
- name: Checkout
uses: actions/checkout@v4
- name: Build draft PDF
uses: openjournals/openjournals-draft-action@master
with:
journal: joss
# This should be the path to the paper within your repo.
paper-path: paper/paper.md
- name: Upload
uses: actions/upload-artifact@v4
with:
name: paper
# This is the output path where Pandoc will write the compiled
# PDF. Note, this should be the same directory as the input
# paper.md
path: paper.pdf
33 changes: 32 additions & 1 deletion paper/paper.md
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---
title: 'ratesb_python: A Python Package for Analyzing Rate Laws in Biological Models'
tags:
- Python
- SBML
- Systems Biology
- Kinetics
- Rate Laws
authors:
- name: Longxuan Fan
orcid: 0009-0006-6523-8302
affiliation: 1
- name: Joseph L. Hellerstein
affiliation: 2
- name: Herbert M. Sauro
affiliation: 3
affiliations:
- name: Viterbi School of Engineering, University of Southern California
index: 1
- name: eScience Institute, University of Washington
index: 2
- name: Department of Bioengineering, University of Washington
index: 3
date: 14 October 2024
bibliography: paper.bib
---

# Summary

`ratesb_python` is a Python package that analyzes mechanistic models of biological systems that consist of networks of chemical reactions like $2 H_2 + O_2 \rightarrow 2 H_2O$ [with rate laws such as $k [h_2]^2 [O_2]$ that describe the rate at which the reaction proceeds]. The package focuses on rate laws of reactions, algebraic expressiona that specify the rate at which reactants (e.g., $H_2, O_2$) are converted into products (e.g., $O_2$). ``ratesb_python`` analyzes rate laws to detect errors and warnings that affect the robustness and accuracy of models that use the SBML (Systems Biology Markup Language) community standard for model model descriptions [@Hucka2003].
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# Future Work

Future developments for `ratesb_python` include enriching the library of checks and optimizing the performance of classification algorithms. The goal is to expand the tool's capabilities, making it a more comprehensive resource for developers and researchers alike, and to introduce customization options for error and warning management, further enhancing its utility in systems biology.
Future developments for `ratesb_python` include enriching the library of checks and optimizing the performance of classification algorithms. The goal is to expand the tool's capabilities, making it a more comprehensive resource for developers and researchers alike, and to introduce customization options for error and warning management, further enhancing its utility in systems biology.

---
bibliography: paper.bib
---
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25 changes: 25 additions & 0 deletions paper/paper.yaml
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title: 'ratesb_python: A Python Package for Analyzing Rate Laws in Biological Models'
tags:
- Python
- SBML
- Systems Biology
- Kinetics
- Rate Laws
authors:
- name: "Longxuan Fan"
orcid: "0009-0006-6523-8302"
affiliation: 1
- name: "Joseph L. Hellerstein"
affiliation: 2
- name: "Herbert M. Sauro"
affiliation: 3
affiliations:
- name: "Viterbi School of Engineering, University of Southern California"
index: 1
- name: "eScience Institute, University of Washington"
index: 2
- name: "Department of Bioengineering, University of Washington"
index: 3
date: 2024-10-14
bibliography: paper.bib
repository: "https://github.com/sys-bio/ratesb_python"

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