Evidence map›Paper›PMID 41479121›Full record

ReviewExperientia supplementum (2012)2026

Bioinformatics Approaches in Noncoding RNAs Research.

Fariya Khan, Ajay Kumar, Salman Akhtar

Abstract readReview
PubMed Publisher
In one paragraph

Review in Experientia supplementum (2012), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Fariya KhanDepartment of Bioengineering, Integral University, Lucknow, India.
Ajay KumarDepartment of Biotechnology, Faculty of Engineering and Technology, Rama University, Kanpur, Uttar Pradesh, India.
Salman AkhtarDepartment of Bioengineering, Integral University, Lucknow, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, noncoding RNAs have sparked significant interest in understanding the diverse roles of ncRNAs in cellular regulation and disease processes. Noncoding RNAs (ncRNAs), encompassing small noncoding RNAs (sncRNAs) and long noncoding RNAs (lncRNAs), are critical regulators of gene expression, epigenetic modifications, and various cellular processes within the human genome. The diverse nature ncRNAs, along with certain complex features, has made them difficult to study through traditional experimental methods. As a result, bioinformatics tools have expanded the possibilities for offering new insights through advanced computational strategies. This chapter explores the recent advancements in ncRNA databases, emphasizing their importance and the innovative in silico strategies that enable the prediction and analysis of biological interactions, particularly for miRNAs and lncRNAs. It offers an in-depth overview of the structural properties, classification, and functions of various types of noncoding RNAs, highlighting their crucial roles in cellular processes. Additionally, the chapter discusses the significant therapeutic potential of ncRNAs, focusing on their applications in treating cancer and other severe diseases. These insights are pivotal in advancing the development of targeted therapies and precision medicine.

Indexed as

Computational BiologyMicroRNAsNeoplasmsRNA, Long NoncodingRNA, UntranslatedEpigenesis, GeneticHumansMicroRNAsRNA, Long NoncodingRNA, UntranslatedBioinformaticsEpigeneticsGenomeIn silicolncRNAmiRNAncRNAsncRNATranscriptome

Identifiers

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.