Predicting the stability of profiling signals of small RNAs

Fuente: arXiv
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Hauptverfasser: Li, Qiuyun, Riehl, Manda
Format: Preprint
Veröffentlicht: 2024
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author Li, Qiuyun
Riehl, Manda
author_facet Li, Qiuyun
Riehl, Manda
contents Profiling is a process that finds similarities between different RNA secondary structures by extracting signals from the Boltzmann sampling. The reproducibility of profiling can be identified by the standard deviation of number of features among Boltzmann samples. We found a strong relationship between the frequency of each helix class and its standard deviation of the frequency upon repeated Boltzmann sampling. We developed a perturbation technique to predict the stability of these featured helix classes without the need for repeated Boltzmann sampling, with accuracy between 84% and 94%, depending on the type of RNA. Our technique only requires 0.2% of the computation time compared to one profiling process.
format Preprint
id arxiv_https___arxiv_org_abs_2403_12827
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Predicting the stability of profiling signals of small RNAs
Li, Qiuyun
Riehl, Manda
Biomolecules
92B05
Profiling is a process that finds similarities between different RNA secondary structures by extracting signals from the Boltzmann sampling. The reproducibility of profiling can be identified by the standard deviation of number of features among Boltzmann samples. We found a strong relationship between the frequency of each helix class and its standard deviation of the frequency upon repeated Boltzmann sampling. We developed a perturbation technique to predict the stability of these featured helix classes without the need for repeated Boltzmann sampling, with accuracy between 84% and 94%, depending on the type of RNA. Our technique only requires 0.2% of the computation time compared to one profiling process.
title Predicting the stability of profiling signals of small RNAs
topic Biomolecules
92B05
url https://arxiv.org/abs/2403.12827