ArticleResearch square2023
Extending the toolbox for RNA biology with SegModTeX: A polymerase-driven method for site-specific and segmental labeling of RNA.
Article in Research square, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
- Updated by
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
RNA performs a wide range of functions regulated by its structure, dynamics, and often post-transcriptional modifications. While NMR is the leading method for understanding RNA structure and dynamics, it is currently limited by the inability to reduce spectral crowding by efficient segmental labeling. Furthermore, because of the challenging nature of RNA chemistry, the tools being developed to introduce site-specific modifications are increasingly complex and laborious. Here we use a previously designed
Identifiers
What OpenQuestion holds
Registered trials
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.