Structural data used to train, test, and characterize a new geometric deep learning RNA scoring function
Abstract/Contents
- Abstract
- What is in this directory?--------------------------blind.tar => blind/RNA Puzzles challenges 24, 26, 27, and 28 datasets.paper_notebooks.tar => paper_notebooks/Data analysis code to replicate plots in paper.rnaome.tar => rnaome/Non-redundant set of RNAs dataset.translation.tar => translation/Helix translation dataset.augmented_puzzles.tar => augmented_puzzles/Augmented Puzzles dataset.classics_train_val.tar => classics_train_val/Training data from FARFAR2-Classics
Description
| Type of resource | software, multimedia |
|---|---|
| Date created | 2020 |
| Publication date | 2021 |
Creators/Contributors
| Author | Townshend, Raphael J. L. |
https://orcid.org/https://orcid.org/0000-0001-6362-1451
(unverified)
|
|---|---|---|
| Author | Watkins, Andrew M. |
https://orcid.org/https://orcid.org/0000-0003-1617-1720
(unverified)
|
| Author | Eismann, Stephan | |
| Author | Rangan, Ramya | |
| Author | Karelina, Masha |
https://orcid.org/https://orcid.org/0000-0003-1880-4536
(unverified)
|
| Author | Das, Rhiju |
https://orcid.org/https://orcid.org/0000-0001-7497-0972
(unverified)
|
| Author | Dror, Ron O. |
https://orcid.org/https://orcid.org/0000-0002-6418-2793
(unverified)
|
Subjects
| Subject | Biochemistry |
|---|---|
| Subject | RNA structure |
| Subject | fragment assembly |
| Subject | blind prediction |
| Subject | computer science |
| Subject | deep learning |
| Genre | Dataset |
| Genre | Quantitative data |
| Genre | Quantitative data |
Bibliographic information
| Related item | |
|---|---|
| DOI | https://doi.org/10.25740/bn398fc4306 |
| Location | https://purl.stanford.edu/bn398fc4306 |
Access conditions
- Use and reproduction
- User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.
- License
- This work is licensed under a Creative Commons Attribution Share Alike 3.0 Unported license (CC BY-SA).
Preferred citation
- Preferred citation
- Townshend, Raphael J. L. and Watkins, Andrew M. and Eismann, Stephan and Rangan, Ramya and Karalina, Masha and Das, Rhiju and Dror, Ron O. (2020). Structural data used to train, test, and characterize a new geometric deep learning RNA scoring function. Stanford Digital Repository. Available at: https://purl.stanford.edu/bn398fc4306 https://doi.org/10.25740/bn398fc4306
Collection
Stanford Research Data
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- Contact
- watkina6@gene.com
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