Computational Modeling Skills
Computational Modeling Skills is a collection of skills for scientific workflows used frequently and repeatedly in biophysics theoretical modeling. These skills aid in critically brainstorming and reviewing models to test hypotheses, doing linear stability analysis, writing structured Jupyter notebooks, making publication-quality plots, designing scientifically accurate concept diagrams and schematics, documenting code and models during model development, and running large simulation jobs in HPC.
My goal for making these skills is not to replace the scientist but only to aid them. If you are new to research then please use this skill to learn the process instead of bypassing the rigorous scientific training and thought. The main purpose is to automate repetitive workflows so that researchers can engage in what they are supposed to do: generating hypotheses and finding smart ways to test them. The point of this structured workflow is not to increase productivity, but to make computational research reproducible, reviewable, tractable, and more structured.
| Skill | Scope |
|---|---|
| computational-modeling | Develop, test, and review scientific models for hypothesis testing, numerical verification, and physical validation |
| model-documentation | Write and audit model documents explaining physical assumptions, equations, and numerical methods |
| scientific-notebook | Create, maintain, execute, and review Jupyter notebooks for scientific research |
| linear-stability-analysis | Derive, compute, plot, and report linear stability of stationary states in 1D or 2D continuum systems |
| data-visualization | Create and refine publication-quality quantitative plots from completed scientific data, including notebook figures |
| schematic-designer | Design scientifically faithful figures and schematics with editable sources, PDF, and outlined SVG |
| paper-reproduce | Reproduce, assess, or apply a paper’s computational model, method, claims, or results |
| lets-be-clear | Clarify decisions, confirm the scope, and complete the agreed task |
| slurm | Prepare, submit, inspect, and cancel one CPU batch job with native Slurm |
Schematic designer example
Complementary modeling choices for collective cells: particle dynamics, cell states and rules, lattice representations, cell-shape or density fields, and coupled cells, chemical fields, and extracellular matrix.
Paper reproduction decisions
Choose a primary objective—reproduction, assessment, or application—and a target depth—model, claim, or result.
Choose one objective and one depth for each target; the depths are alternatives. Workflow.
Original material uses the MIT license. See third-party notices.