Tuning a predictive DNA replication programming computational model for Trypanosomatids - Scholl, Bruno B.; Palma, Ligia C.; Hariki, Victor S.; Elias, Maria Carolina; Reis, Marcelo S. (Anais do Simpósio Brasileiro de Bioinformática (BSB), 2024)
In this paper, we report the tuning of a predictive DNA replication programming computational model for both Trypanosoma brucei and Trypanosoma cruzi, unicellular protozoan endoparasites that cause African sleeping sickness and Chagas disease, respectively. This is a stochastic dynamic model for simulating the DNA replication process with concomitant constitutive transcription, enabling the analysis of the interactions between replication and transcription in these organisms. Using Optuna, an open-source hyperparameter optimizer, we explored almost 5,000 parameter combinations across both trainings of the models, each with up to 1,000 simulations averaged as the output, yielding two models that deviate by only 7.9% and 5.55% compared to experimental MFA-Seq data for T. brucei and T. cruzi, respectively, according to the SMAPE metric. The results also indicate a pattern in both models, in which the head-on collisions between replication and transcription machineries are co-localized with bases replicated earlier in the S-phase. This work paves the way for further in silico experimental exploration, aiming to unravel underlying mechanisms of the DNA replication programming in trypanosomatids.