Digital Organism Simulation Environment (DOSE) Version 1.0.4.

Citation: Castillo, CFG, Ling, MHT. 2018. Digital Organism Simulation Environment (DOSE) Version 1.0.4. In Current STEM, Volume 1, page 1-106. Nova Science Publishers, Inc. ISBN 978-1-53613-416-2.

Evolution is a fundamental aspect of biology but examining evolution is difficult, time-consuming and costly. At the same time, molecular analysis of biological organisms is generally destructive, which presents a conundrum between observing possible evolutionary outcomes and in depth molecular analysis to decipher the corresponding evolutionary outcomes. Artificial life simulations via the use of digital organisms (DO) had been proposed as a feasible means of examining evolution in silico and had yield biologically relevant findings. Being digital, identical replicates can be made for analysis; thereby, resolving the conundrum. Recently, original implementation of DOSE (Ling, 2012a) had been improved (Castillo and Ling, 2014a) for use as a Python library for simplified construction of simulation, enabling database logging and revival of simulations. This manuscript documents the implementation and improvement of DOSE, which is released as DOSE version 1.0.4 (https://github.com/mauriceling/dose/releases/tag/v1.0.4) and licensed under GNU General Public License version 3. DOSE codebase is hosted and available for forking at https://github.com/mauriceling/dose.