paper.md

title	tags	authors	affiliations	date	bibliography
FEArS: a python package for simulating evolution on arbitrary fitness seascapes	Python evolution fitness landscape fitness seascape	name orcid affiliation Eshan S. King 0000-0002-0345-3780 1 name orcid affiliation Davis T. Weaver 0000-0003-3086-497X 1 name corresponding affiliation orcid Jacob G. Scott true 2 0000-0003-2971-7673	name index Systems Biology and Bioinformatics Program, Case Western Reserve University School of Medicine, USA 1 name index Translational Hematology Oncology Research, Cleveland Clinic Lerner Research Institute, USA 2	03 November 2022	paper.bib

Summary

The evolution of drug resistance across kingdoms, including in cancer and infectious disease, is governed by the same fundamental laws. Modeling evolution with genotype-specific dose response curves, collectively forming a 'fitness seascape' enables simulations that include realistic pharmacokinetic constraints, more closely resembling the environmental conditions within a patient. FEArS (Fast Evolution on Arbitrary Seascapes) is a python package that enables simulating evolution with fitness seascapes. FEArS can simulate a wide variety of experimental conditions with many arbitrary biological parameters. FEArS remains computationally efficient despite being an agent-based model, even for very large population sizes. FEArS also contains powerful and flexible utilities for data analysis, plotting, and experimental fitness seascape estimation.

Statement of need

Gala is an Astropy-affiliated Python package for galactic dynamics. Python enables wrapping low-level languages (e.g., C) for speed without losing flexibility or ease-of-use in the user-interface. The API for Gala was designed to provide a class-based and user-friendly interface to fast (C or Cython-optimized) implementations of common operations such as gravitational potential and force evaluation, orbit integration, dynamical transformations, and chaos indicators for nonlinear dynamics. Gala also relies heavily on and interfaces well with the implementations of physical units and astronomical coordinate systems in the Astropy package [@astropy] (astropy.units and astropy.coordinates).

Gala was designed to be used by both astronomical researchers and by students in courses on gravitational dynamics or astronomy. It has already been used in a number of scientific publications [@Pearson:2017] and has also been used in graduate courses on Galactic dynamics to, e.g., provide interactive visualizations of textbook material [@Binney:2008]. The combination of speed, design, and support for Astropy functionality in Gala will enable exciting scientific explorations of forthcoming data releases from the Gaia mission [@gaia] by students and experts alike.

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Acknowledgements

We acknowledge contributions from Brigitta Sipocz, Syrtis Major, and Semyeong Oh, and support from Kathryn Johnston during the genesis of this project.

References