AIMC Topic: RNA, Long Noncoding

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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...

A deep recurrent neural network discovers complex biological rules to decipher RNA protein-coding potential.

Nucleic acids research
The current deluge of newly identified RNA transcripts presents a singular opportunity for improved assessment of coding potential, a cornerstone of genome annotation, and for machine-driven discovery of biological knowledge. While traditional, featu...

miRandola 2017: a curated knowledge base of non-invasive biomarkers.

Nucleic acids research
miRandola (http://mirandola.iit.cnr.it/) is a database of extracellular non-coding RNAs (ncRNAs) that was initially published in 2012, foreseeing the relevance of ncRNAs as non-invasive biomarkers. An increasing amount of experimental evidence shows ...

FARNA: knowledgebase of inferred functions of non-coding RNA transcripts.

Nucleic acids research
Non-coding RNA (ncRNA) genes play a major role in control of heterogeneous cellular behavior. Yet, their functions are largely uncharacterized. Current available databases lack in-depth information of ncRNA functions across spectrum of various cells/...

FMLNCSIM: fuzzy measure-based lncRNA functional similarity calculation model.

Oncotarget
Accumulating experimental studies have indicated the influence of lncRNAs on various critical biological processes as well as disease development and progression. Calculating lncRNA functional similarity is of high value in inferring lncRNA functions...