Insights into Online microRNA Bioinformatics Tools

Buitrago, Diana Luna; Lovering, Ruth C.; Caporali, Andrea

doi:10.3390/ncrna9020018

Cited by 11 publications

(4 citation statements)

References 110 publications

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“…Some miRNA transcription initiators have been identified [53] -giving potential insight into why certain miRNAs are selected based upon various challenges. Of the 27 500 known human ncRNAs there are more than 1881 miRNA precursor sequences in the human genome, allowing the generation of 2588 mature miRNAs of which 200 are associated with at least one mRNA [56]. ncRNAs are expressed in different tissues and cell types that can interact with target mRNAs, through base-pairing, to inhibit their translation [54][55][56].…”

Section: The Central Role Of Small Non-coding Rnas In Gene Expressionmentioning

confidence: 99%

“…Of the 27 500 known human ncRNAs there are more than 1881 miRNA precursor sequences in the human genome, allowing the generation of 2588 mature miRNAs of which 200 are associated with at least one mRNA [56]. ncRNAs are expressed in different tissues and cell types that can interact with target mRNAs, through base-pairing, to inhibit their translation [54][55][56]. miRNAs are powerful regulators of cellular activities including cell growth, differentiation, development, proliferation and death, apoptosis, fat metabolism, neuronal patterning, hematopoietic differentiation, and in immune function [57].…”

Section: The Central Role Of Small Non-coding Rnas In Gene Expressionmentioning

confidence: 99%

See 1 more Smart Citation

Effect of Age, Sex, and COVID-19 Vaccination History on All-Cause Mortality: Unexpected Outcomes in a Complex Biological and Social System

Jones¹,

Ponomarenko²

2023

Preprint

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All vaccines exhibit both specific and non-specific effects. The specific effects are measured by the efficacy against the target pathogen, while the non-specific effects can be detected by the change in all-cause mortality . All-cause mortality data (gender, age band, vaccination history, month of death) between January 2021 and May 2022 was compiled by the Office for National Statistics. COVID–19 vaccination gave good protection on many occasions but less so for younger ages. Each gender and age group shows its own unique vaccination benefit/disbenefit time profile. Individuals are free to make vaccination decisions. For example, women aged 18-39 show a cohort who do not progress beyond the first or second dose. The all-cause mortality outcomes for the Omicron variant showed a very poor response to vaccination with 70% of sex/age/vaccination stage/month combinations increasing all-cause mortality, probably due to unfavorable antigenic distance between the first-generation vaccines and this variant, and additional non-specific effects. The all-cause mortality outcomes of COVID–19 vaccination is far more nuanced than have been widely appreciated, and virus vector appear better than the mRNA vaccines in this specific respect. The latter are seemingly more likely to increase all-cause mortality especially in younger age groups. An extensive discussion/literature review is included to provide potential explanations for the observed unexpected vaccine effects.

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Section: The Central Role Of Small Non-coding Rnas In Gene Expressionmentioning

confidence: 99%

Section: The Central Role Of Small Non-coding Rnas In Gene Expressionmentioning

confidence: 99%

Effect of Age, Sex, and COVID-19 Vaccination History on All-Cause Mortality: Unexpected Outcomes in a Complex Biological and Social System

Jones¹,

Ponomarenko²

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…The miRNA seed sequence is one of the main miRNA features used in target prediction algorithms, along with thermodynamic stability/free energy, evolutionary conservation, target site abundance, and accessibility of the target site [145]. Moreover, as with identification tools, ML algorithms have been developed for predicting novel targets.…”

Section: Target Predictionmentioning

confidence: 99%

Hepatitis B Virus and microRNAs: A Bioinformatics Approach

Zulian,

Fiscon,

Paci

et al. 2023

IJMS

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In recent decades, microRNAs (miRNAs) have emerged as key regulators of gene expression, and the identification of viral miRNAs (v-miRNAs) within some viruses, including hepatitis B virus (HBV), has attracted significant attention. HBV infections often progress to chronic states (CHB) and may induce fibrosis/cirrhosis and hepatocellular carcinoma (HCC). The presence of HBV can dysregulate host miRNA expression, influencing several biological pathways, such as apoptosis, innate and immune response, viral replication, and pathogenesis. Consequently, miRNAs are considered a promising biomarker for diagnostic, prognostic, and treatment response. The dynamics of miRNAs during HBV infection are multifaceted, influenced by host variability and miRNA interactions. Given the ability of miRNAs to target multiple messenger RNA (mRNA), understanding the viral–host (human) interplay is complex but essential to develop novel clinical applications. Therefore, bioinformatics can help to analyze, identify, and interpret a vast amount of miRNA data. This review explores the bioinformatics tools available for viral and host miRNA research. Moreover, we introduce a brief overview focusing on the role of miRNAs during HBV infection. In this way, this review aims to help the selection of the most appropriate bioinformatics tools based on requirements and research goals.

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“…Since there are many useful tools available, it is a daunting task to search and investigate each tool. To address this point, Buitrago et al nicely summarize the currently available online tools for miRNAs [ 1 ].…”

mentioning

confidence: 99%