2021
DOI: 10.1371/journal.pone.0244858
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Probabilistic models of biological enzymatic polymerization

Abstract: In this study, hierarchies of probabilistic models are evaluated for their ability to characterize the untemplated addition of adenine and uracil to the 3’ ends of mitochondrial mRNAs of the human pathogen Trypanosoma brucei, and for their generative abilities to reproduce populations of these untemplated adenine/uridine “tails”. We determined the most ideal Hidden Markov Models (HMMs) for this biological system. While our HMMs were not able to generatively reproduce the length distribution of the tails, they … Show more

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Cited by 3 publications
(4 citation statements)
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“…Two enzymes add nucleotides to mRNA 3′ ends: KPAP1 adds As and KRET1 adds Us. To investigate how A and U addition may be different for circRNA and total RNA, we used hidden Markov modelling (HMM) 19 . To define the number of nucleotide addition ‘states’ required for HMM, the two types of mRNA tails on kinetoplastid mitochondrial mRNAs must be considered.…”
Section: Resultsmentioning
confidence: 99%
“…Two enzymes add nucleotides to mRNA 3′ ends: KPAP1 adds As and KRET1 adds Us. To investigate how A and U addition may be different for circRNA and total RNA, we used hidden Markov modelling (HMM) 19 . To define the number of nucleotide addition ‘states’ required for HMM, the two types of mRNA tails on kinetoplastid mitochondrial mRNAs must be considered.…”
Section: Resultsmentioning
confidence: 99%
“…Hidden Markov modelling (HMM) was performed as described in (Gazestani et al, 2018) and (Hampton et al, 2021). To ensure consistency, models were trained hierarchically, with additional randomized states added one at a time after fully training the submodel, using the Baum-Welch algorithm.…”
Section: Hidden Markov Modellingmentioning
confidence: 99%
“…To further investigate how A and U addition differ when the KPAPs are manipulated, we used hidden Markov models (HMMs), as previously implemented to describe tail addition et al, 2016; Gazestani et al, 2018;Hampton et al, 2021;Smoniewski et al, 2023). We use HMMs to elucidate how the polymerases are acting during in-and ex-tail addition, as they are very sensitive to differences between libraries.…”
Section: Hidden Markov Modelling -Kpap1 and Kpap2mentioning
confidence: 99%
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