Evidence map›Paper›PMID 29657273›Full record

ReviewNon-coding RNA2016

Recent Advances in Identification of RNA Modifications.

Wei Chen, Hao Lin

Open access · goldAbstract readReview
In one paragraph

Review in Non-coding RNA, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.7field-weighted citation impact, top 15% of its field
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

6 citing papers in PubMed, 17 citations in OpenAlex.

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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

2 authors at 2 institutions in 1 country.

Wei ChenDepartment of Physics, School of Sciences, and Center for Genomics and Computational Biology, North China University of Science and Technology, Tangshan 063000, China. chenweiimu@gmail.com.
Hao LinKey Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China. hlin@uestc.edu.cn.ORCID 0000-0001-6265-2862
North China University of Science and Technology · CNUniversity of Electronic Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RNA modifications are involved in a broad spectrum of biological and physiological processes. To reveal the functions of RNA modifications, it is important to accurately predict their positions. Although high-throughput experimental techniques have been proposed, they are cost-ineffective. As good complements of experiments, many computational methods have been proposed to predict RNA modification sites in recent years. In this review, we will summarize the existing computational approaches directed at predicting RNA modification sites. We will also discuss the challenges and future perspectives in developing reliable methods for predicting RNA modification sites.

Indexed as

N1-methyladenosineN6-methyladenosinepseudouridineRNA modification

Identifiers

PMID29657273
PMCPMC5831996
OpenAlexW2563432111

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.