The “guiding” principles of noncoding <scp>RNA</scp> function

Deogharia, Manisha; Gurha, Priyatansh

doi:10.1002/wrna.1704

Cited by 36 publications

(24 citation statements)

References 153 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…RNAs can also interact with other RNAs and several studies have shown these interactions to be crucially involved in the regulation of gene transcription, cell metabolism, and other key cellular functions (Deogharia and Gurha, 2021;Singh et al, 2022;Wang et al, 2022). Despite the fact that a large number of RNA-RNA interactions have been experimentally validated, many more have yet to be identified.…”

Section: Computational Methods For Rna-rna Interactions Predictionmentioning

confidence: 99%

Artificial intelligence methods enhance the discovery of RNA interactions

Pepe

Appierdo²,

Carrino³

et al. 2022

Front. Mol. Biosci.

View full text Add to dashboard Cite

Understanding how RNAs interact with proteins, RNAs, or other molecules remains a challenge of main interest in biology, given the importance of these complexes in both normal and pathological cellular processes. Since experimental datasets are starting to be available for hundreds of functional interactions between RNAs and other biomolecules, several machine learning and deep learning algorithms have been proposed for predicting RNA-RNA or RNA-protein interactions. However, most of these approaches were evaluated on a single dataset, making performance comparisons difficult. With this review, we aim to summarize recent computational methods, developed in this broad research area, highlighting feature encoding and machine learning strategies adopted. Given the magnitude of the effect that dataset size and quality have on performance, we explored the characteristics of these datasets. Additionally, we discuss multiple approaches to generate datasets of negative examples for training. Finally, we describe the best-performing methods to predict interactions between proteins and specific classes of RNA molecules, such as circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs), and methods to predict RNA-RNA or RNA-RBP interactions independently of the RNA type.

show abstract

Section: Computational Methods For Rna-rna Interactions Predictionmentioning

confidence: 99%

Artificial intelligence methods enhance the discovery of RNA interactions

Pepe

Appierdo²,

Carrino³

et al. 2022

Front. Mol. Biosci.

View full text Add to dashboard Cite

show abstract

“…Beyond the developments as reviewed in section 2.3, a further level of complexityi.e. the human epigenome and its life-time dynamics in health and cardiovascular disease [84,[146][147][148][149][150][151][152][153][154][155] -emerged as holding promise for possible therapeutic exploitation [114-120, 156, 157]. At the present time, however, the impact of epigenetic drugs upon clinical medicine is still limited as compared to the nucleic acid drugs discussed above.…”

Section: Continuously Emerging New Levels Of Complexity Of the Human ...mentioning

confidence: 99%

Innate Immunity in Cardiovascular Diseases – Identification of Novel Molecular Players and Targets

Poller¹,

Heidecker²,

Ammirati³

et al. 2022

Preprint

View full text Add to dashboard Cite

During the past few years unexpected developments have driven studies in the field of clinical immunology. One driver of immense impact was the outbreak of a pandemic caused by the novel virus SARS-CoV-2. Excellent recent reviews address diverse aspects of immunological re-search into cardiovascular diseases. Here, we specifically focus on selected studies taking ad-vantage of advanced state-of-the-art molecular genetic methods ranging from genome-wide epi/transcriptome mapping and variant scanning to optogenetics and chemogenetics. First, we discuss emerging clinical relevance of advanced diagnostics for cardiovascular diseases - includ-ing those associated with COVID-19 - with a focus on the role of inflammation in cardiomyopa-thies and arrhythmias. Second, we consider newly identified immunological interactions at or-gan and systems level which affect cardiovascular pathogenesis. Thus, studies into immune in-fluences arising from the intestinal system are moving towards therapeutic exploitation. Fur-ther, powerful new research tools have enabled novel insight into brain – immune system inter-actions at unprecedented resolution. This latter line of investigation emphasizes the strength of influence of emotional stress - acting through defined brain regions - upon viral and cardiovas-cular disorders. Several challenges need to be overcome before the full impact of these far-reaching new findings will hit the clinical arena.

show abstract

“…Noncoding RNAs (ncRNAs) primarily include microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs) ( Jusic et al, 2020 ; Deogharia and Gurha 2021 ; Rahimian et al, 2021 ). The ncRNAs bind to multiple molecular targets to form regulatory networks in various biological activities, including initiating specific cellular biological responses, regulating gene expression, intracellular signaling, and epigenetic modifications ( Ding et al, 2021 ; Ducoli and Detmar 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Noncoding RNAs in the Glycolysis of Ovarian Cancer

Zhang

Liu

2022

Front. Pharmacol.

View full text Add to dashboard Cite

Energy metabolism reprogramming is the characteristic feature of tumors. The tumorigenesis, metastasis, and drug resistance of ovarian cancer (OC) is dependent on energy metabolism. Even under adequate oxygen conditions, OC cells tend to convert glucose to lactate, and glycolysis can rapidly produce ATP to meet their metabolic energy needs. Non-coding RNAs (ncRNAs) interact directly with DNA, RNA, and proteins to function as an essential regulatory in gene expression and tumor pathology. Studies have shown that ncRNAs regulate the process of glycolysis by interacting with the predominant glycolysis enzyme and cellular signaling pathway, participating in tumorigenesis and progression. This review summarizes the mechanism of ncRNAs regulation in glycolysis in OC and investigates potential therapeutic targets.

show abstract

The “guiding” principles of noncoding RNA function

Cited by 36 publications

References 153 publications

Artificial intelligence methods enhance the discovery of RNA interactions

Artificial intelligence methods enhance the discovery of RNA interactions

Innate Immunity in Cardiovascular Diseases – Identification of Novel Molecular Players and Targets

Noncoding RNAs in the Glycolysis of Ovarian Cancer

Contact Info

Product

Resources

About