BiologybioRxiv
Ranked by formulaVerdict: NotableNuFold RNA Structure Database: Large-Scale RNA Tertiary Structure Prediction with Confidence Metrics
To bridge the gap between rapid RNA sequence discovery and slow experimental characterization, we present the NuFold RNA Structure Database (https://nufold.kiharalab.org/), a resource providing large-scale…
Caveats
- Preprint; not yet peer reviewed.
VerdictWorth a reader's time today.
Abstract
Summary: To bridge the gap between rapid RNA sequence discovery and slow experimental characterization, we present the NuFold RNA Structure Database (https://nufold.kiharalab.org/), a resource providing large-scale, precomputed full-atom RNA tertiary structures. By removing the computational barriers associated with running the method locally, this database makes high-accuracy RNA structure models readily accessible to the biological research community for a wide range of applications. Availability and implementation: All predicted structures and corresponding data are available at https://nufold.kiharalab.org/. The source code for the NuFold program is available at https://github.com/kiharalab/NuFold. Supplementary Information: For more insight into resulting statistics gathered for this project, see https://nufold.kiharalab.org/statistics. For more insight into how to utilize the webserver itself, see https://nufold.kiharalab.org/faq and https://nufold.kiharalab.org/tutorial.
The editor's rubric
- Leverage4 / 5
- A general-purpose tool used across several fields (Adam, ResNet, LoRA, next-generation sequencing).
- Magnitude2 / 5
- Solid incremental gain on a meaningful problem.
- Evidence3 / 5
- Solid: multiple benchmarks or cohorts, ablations, fair baselines, released code or data.
- Novelty3 / 5
- A genuinely new approach to an open problem.
- Trajectory3 / 5
- A clear path to scale.
- Stakes2 / 5
- Benefits a professional community (practitioners, clinicians, engineers).
Editor’s rationale
Heuristic triage from title and abstract text only, not a reading of the paper. Cues found: method (we propose); breadth (wide range); novelty (discovery); verification (experimental validation, code released); scale (scalable).
How the score was computed
Desks place stronger verdicts first, then use this score to order work within the same verdict.
- Merit
- 6.0 / 10
- Adjusted merit
- 4.8 / 10
- Attention
- 0%
- Freshness
- 88%