AIMC Topic: RNA, Long Noncoding
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MLCDForest: multi-label classification with deep forest in disease prediction for long non-coding RNAs.
Briefings in bioinformatics
May 20, 2021
The long non-coding RNAs (lncRNAs) are subject of intensive recent studies due to its association with various human diseases. It is desirable to build the artificial intelligence-based models for prediction of diseases or tissues based on the lncRNA...
DeepCPP: a deep neural network based on nucleotide bias information and minimum distribution similarity feature selection for RNA coding potential prediction.
Briefings in bioinformatics
Mar 22, 2021
The development of deep sequencing technologies has led to the discovery of novel transcripts. Many in silico methods have been developed to assess the coding potential of these transcripts to further investigate their functions. Existing methods per...
m6A-Atlas: a comprehensive knowledgebase for unraveling the N6-methyladenosine (m6A) epitranscriptome.
Nucleic acids research
Jan 8, 2021
N 6-Methyladenosine (m6A) is the most prevalent RNA modification on mRNAs and lncRNAs. It plays a pivotal role during various biological processes and disease pathogenesis. We present here a comprehensive knowledgebase, m6A-Atlas, for unraveling the ...
Gene set analysis methods for the functional interpretation of non-mRNA data-Genomic range and ncRNA data.
Briefings in bioinformatics
Sep 25, 2020
Gene set analysis (GSA) is one of the methods of choice for analyzing the results of current omics studies; however, it has been mainly developed to analyze mRNA (microarray, RNA-Seq) data. The following review includes an update regarding general me...
DeepLGP: a novel deep learning method for prioritizing lncRNA target genes.
Bioinformatics (Oxford, England)
Aug 15, 2020
MOTIVATION: Although long non-coding RNAs (lncRNAs) have limited capacity for encoding proteins, they have been verified as biomarkers in the occurrence and development of complex diseases. Recent wet-lab experiments have shown that lncRNAs function ...
Screening key lncRNAs with diagnostic and prognostic value for head and neck squamous cell carcinoma based on machine learning and mRNA-lncRNA co-expression network analysis.
Cancer biomarkers : section A of Disease markers
Jan 1, 2020
BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is the seventh most common type of cancer around the world. The aim of this study was to seek the long non-coding RNAs (lncRNAs) acting as diagnostic and prognostic biomarker of HNSCC.
Recent Advances on the Semi-Supervised Learning for Long Non-Coding RNA-Protein Interactions Prediction: A Review.
Protein and peptide letters
Jan 1, 2020
In recent years, more and more evidence indicates that long non-coding RNA (lncRNA) plays a significant role in the development of complex biological processes, especially in RNA progressing, chromatin modification, and cell differentiation, as well ...
circDeep: deep learning approach for circular RNA classification from other long non-coding RNA.
Bioinformatics (Oxford, England)
Jan 1, 2020
MOTIVATION: Over the past two decades, a circular form of RNA (circular RNA), produced through alternative splicing, has become the focus of scientific studies due to its major role as a microRNA (miRNA) activity modulator and its association with va...
[Methylation level of MEG3 and semen quality].
Zhonghua nan ke xue = National journal of andrology
Nov 1, 2019
OBJECTIVE: To study the relationship between semen quality and the methylation level of maternally expressed gene 3 (MEG3) in sperm.
Uncovering the mouse olfactory long non-coding transcriptome with a novel machine-learning model.
DNA research : an international journal for rapid publication of reports on genes and genomes
Aug 1, 2019
Very little is known about long non-coding RNAs (lncRNAs) in the mammalian olfactory sensory epithelia. Deciphering the non-coding transcriptome in olfaction is relevant because these RNAs have been shown to play a role in chromatin modification and ...
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