Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 2 de 2
Filter
Add more filters










Database
Language
Publication year range
1.
Brief Bioinform ; 24(3)2023 05 19.
Article in English | MEDLINE | ID: mdl-37139545

ABSTRACT

The expanding field of epitranscriptomics might rival the epigenome in the diversity of biological processes impacted. In recent years, the development of new high-throughput experimental and computational techniques has been a key driving force in discovering the properties of RNA modifications. Machine learning applications, such as for classification, clustering or de novo identification, have been critical in these advances. Nonetheless, various challenges remain before the full potential of machine learning for epitranscriptomics can be leveraged. In this review, we provide a comprehensive survey of machine learning methods to detect RNA modifications using diverse input data sources. We describe strategies to train and test machine learning methods and to encode and interpret features that are relevant for epitranscriptomics. Finally, we identify some of the current challenges and open questions about RNA modification analysis, including the ambiguity in predicting RNA modifications in transcript isoforms or in single nucleotides, or the lack of complete ground truth sets to test RNA modifications. We believe this review will inspire and benefit the rapidly developing field of epitranscriptomics in addressing the current limitations through the effective use of machine learning.


Subject(s)
Machine Learning , Transcriptome , RNA, Messenger , RNA/genetics
2.
Sci Rep ; 11(1): 3209, 2021 02 05.
Article in English | MEDLINE | ID: mdl-33547380

ABSTRACT

Viral co-infections occur in COVID-19 patients, potentially impacting disease progression and severity. However, there is currently no dedicated method to identify viral co-infections in patient RNA-seq data. We developed PACIFIC, a deep-learning algorithm that accurately detects SARS-CoV-2 and other common RNA respiratory viruses from RNA-seq data. Using in silico data, PACIFIC recovers the presence and relative concentrations of viruses with > 99% precision and recall. PACIFIC accurately detects SARS-CoV-2 and other viral infections in 63 independent in vitro cell culture and patient datasets. PACIFIC is an end-to-end tool that enables the systematic monitoring of viral infections in the current global pandemic.


Subject(s)
COVID-19/diagnosis , Coinfection/diagnosis , Deep Learning , RNA Virus Infections/diagnosis , RNA Viruses/isolation & purification , SARS-CoV-2/isolation & purification , COVID-19 Testing , Coinfection/virology , Coronaviridae/isolation & purification , Humans , Metapneumovirus/classification , Metapneumovirus/isolation & purification , Neural Networks, Computer , Orthomyxoviridae/classification , Orthomyxoviridae/isolation & purification , RNA Virus Infections/virology , RNA Viruses/classification , RNA-Seq , Rhinovirus/classification , Rhinovirus/isolation & purification , SARS-CoV-2/classification , Sensitivity and Specificity
SELECTION OF CITATIONS
SEARCH DETAIL
...