AIMC Topic: RNA, Long Noncoding

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Recent Advances on the Semi-Supervised Learning for Long Non-Coding RNA-Protein Interactions Prediction: A Review.

Protein and peptide letters
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)
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
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
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 ...

DeepCNPP: Deep Learning Architecture to Distinguish the Promoter of Human Long Non-Coding RNA Genes and Protein-Coding Genes.

Studies in health technology and informatics
Promoter region of protein-coding genes are gradually being well understood, yet no comparable studies exist for the promoter of long non-coding RNA (lncRNA) genes which has emerged as a global potential regulator in multiple cellular process and dif...

Enrichment of Up-regulated and Down-regulated Gene Clusters Using Gene Ontology, miRNAs and lncRNAs in Colorectal Cancer.

Combinatorial chemistry & high throughput screening
AIM AND OBJECTIVE: It is interesting to find the gene signatures of cancer stages based on the omics data. The aim of study was to evaluate and to enrich the array data using gene ontology and ncRNA databases in colorectal cancer.

Screening key lncRNAs for human lung adenocarcinoma based on machine learning and weighted gene co-expression network analysis.

Cancer biomarkers : section A of Disease markers
BACKGROUND: Lung adenocarcinoma (LUAD) accounts for a significant proportion of lung cancer and there have been few diagnostic and therapeutic targets for LUAD due to the lack of specific biomarker. The aim of this study was to identify key long non-...

LncADeep: an ab initio lncRNA identification and functional annotation tool based on deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: To characterize long non-coding RNAs (lncRNAs), both identifying and functionally annotating them are essential to be addressed. Moreover, a comprehensive construction for lncRNA annotation is desired to facilitate the research in the fie...

LncRNAnet: long non-coding RNA identification using deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Long non-coding RNAs (lncRNAs) are important regulatory elements in biological processes. LncRNAs share similar sequence characteristics with messenger RNAs, but they play completely different roles, thus providing novel insights for biol...