Evidence map›Paper›PMID 36705903›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2023

Network-Based Structural Alignment of RNA Sequences Using TOPAS.

Chun-Chi Chen, Hyundoo Jeong, Xiaoning Qian, Byung-Jun Yoon

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2023. 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

4 authors.

Chun-Chi ChenDepartment of Electrical Engineering, National Chiayi University, Chiayi City, Taiwan.
Hyundoo JeongDepartment of Mechatronics Engineering, Incheon National University, Incheon, Republic of Korea.
Xiaoning QianDepartment of Electrical and Computer Engineering, Texas A & M University, College Station, TX, USA.
Byung-Jun YoonDepartment of Electrical and Computer Engineering, Texas A & M University, College Station, TX, USA. bjyoon@ece.tamu.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

TOPAS (TOPological network-based Alignment of Structural RNAs) is a network-based alignment algorithm that predicts structurally sound pairwise alignment of RNAs. In order to take advantage of recent advances in comparative network analysis for efficient structurally sound RNA alignment, TOPAS constructs topological network representations for RNAs, which consist of sequential edges connecting nucleotide bases as well as structural edges reflecting the underlying folding structure. Structural edges are weighted by the estimated base-pairing probabilities. Next, the constructed networks are aligned using probabilistic network alignment techniques, which yield a structurally sound RNA alignment that considers both the sequence similarity and the structural similarity between the given RNAs. Compared to traditional Sankoff-style algorithms, this network-based alignment scheme leads to a significant reduction in the overall computational cost while yielding favorable alignment results. Another important benefit is its capability to handle arbitrary folding structures, which can potentially lead to more accurate alignment for RNAs with pseudoknots.

Indexed as

AlgorithmsRNABase SequenceNucleic Acid ConformationSequence AlignmentSequence Analysis, RNARNANetwork alignmentNetwork-based RNA alignmentRNA structural alignment

Identifiers

What OpenQuestion 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 OpenQuestion graph.