{
  "id": 451968,
  "title": "RNA Folding: Research papers on ML models to predict the structures of RNA molecule",
  "url": "/competitions/stanford-ribonanza-rna-folding/discussion/451968",
  "author_name": "C R Suthikshn Kumar",
  "post_date": "2023-10-31T09:28:04.495000",
  "votes": 3,
  "comment_count": 0,
  "views": 0,
  "content": "<p>I am citing here some of the relevant research papers for this competition:</p>\n<ol>\n<li>Marek Justyna, Maciej Antczak, Marta Szachniuk, Machine learning for RNA 2D structure prediction benchmarked on experimental data, Briefings in Bioinformatics, Volume 24, Issue 3, May 2023, bbad153, <a href=\"https://doi.org/10.1093/bib/bbad153\" target=\"_blank\">https://doi.org/10.1093/bib/bbad153</a><br>\nlink: <a href=\"url\" target=\"_blank\">https://academic.oup.com/bib/article/24/3/bbad153/7140288</a></li>\n<li>Nicola Calonaci, et al.,  Machine learning a model for RNA structure prediction, NAR Genomics and Bioinformatics, Volume 2, Issue 4, December 2020, lqaa090, <a href=\"https://doi.org/10.1093/nargab/lqaa090\" target=\"_blank\">https://doi.org/10.1093/nargab/lqaa090</a><br>\nlink: <a href=\"url\" target=\"_blank\">https://academic.oup.com/nargab/article/2/4/lqaa090/5983421</a></li>\n<li>Wang, Xunxun, et al.. \"RNA 3D Structure Prediction: Progress and Perspective\" Molecules 28, no. 14: 5532. <a href=\"https://doi.org/10.3390/molecules28145532\" target=\"_blank\">https://doi.org/10.3390/molecules28145532</a><br>\nlink: <a href=\"url\" target=\"_blank\">https://www.mdpi.com/1420-3049/28/14/5532</a></li>\n<li>Machine learning accurately predicts RNA structures using tiny dataset<br>\nBY TOM METCALFE  7 SEPTEMBER 2021 link: <a href=\"url\" target=\"_blank\">https://www.chemistryworld.com/news/machine-learning-accurately-predicts-rna-structures-using-tiny-dataset/4014347.article</a></li>\n<li>Qi Zhao et al., Review of machine learning methods for RNA secondary structure prediction<br>\nPublished: August 26, 2021<br>\n<a href=\"https://doi.org/10.1371/journal.pcbi.1009291\" target=\"_blank\">https://doi.org/10.1371/journal.pcbi.1009291</a><br>\nlink: <a href=\"url\" target=\"_blank\">https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009291</a></li>\n</ol>\n<p>Some papers were earlier shared on this discussion forum:<br>\n<a href=\"url\" target=\"_blank\">https://www.kaggle.com/competitions/stanford-ribonanza-rna-folding/discussion/437794</a></p>",
  "messages": [
    {
      "id": 2506394,
      "postDate": "2023-10-31T09:28:04.497Z",
      "content": "<p>I am citing here some of the relevant research papers for this competition:</p>\n<ol>\n<li>Marek Justyna, Maciej Antczak, Marta Szachniuk, Machine learning for RNA 2D structure prediction benchmarked on experimental data, Briefings in Bioinformatics, Volume 24, Issue 3, May 2023, bbad153, <a href=\"https://doi.org/10.1093/bib/bbad153\" target=\"_blank\">https://doi.org/10.1093/bib/bbad153</a><br>\nlink: <a href=\"url\" target=\"_blank\">https://academic.oup.com/bib/article/24/3/bbad153/7140288</a></li>\n<li>Nicola Calonaci, et al.,  Machine learning a model for RNA structure prediction, NAR Genomics and Bioinformatics, Volume 2, Issue 4, December 2020, lqaa090, <a href=\"https://doi.org/10.1093/nargab/lqaa090\" target=\"_blank\">https://doi.org/10.1093/nargab/lqaa090</a><br>\nlink: <a href=\"url\" target=\"_blank\">https://academic.oup.com/nargab/article/2/4/lqaa090/5983421</a></li>\n<li>Wang, Xunxun, et al.. \"RNA 3D Structure Prediction: Progress and Perspective\" Molecules 28, no. 14: 5532. <a href=\"https://doi.org/10.3390/molecules28145532\" target=\"_blank\">https://doi.org/10.3390/molecules28145532</a><br>\nlink: <a href=\"url\" target=\"_blank\">https://www.mdpi.com/1420-3049/28/14/5532</a></li>\n<li>Machine learning accurately predicts RNA structures using tiny dataset<br>\nBY TOM METCALFE  7 SEPTEMBER 2021 link: <a href=\"url\" target=\"_blank\">https://www.chemistryworld.com/news/machine-learning-accurately-predicts-rna-structures-using-tiny-dataset/4014347.article</a></li>\n<li>Qi Zhao et al., Review of machine learning methods for RNA secondary structure prediction<br>\nPublished: August 26, 2021<br>\n<a href=\"https://doi.org/10.1371/journal.pcbi.1009291\" target=\"_blank\">https://doi.org/10.1371/journal.pcbi.1009291</a><br>\nlink: <a href=\"url\" target=\"_blank\">https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009291</a></li>\n</ol>\n<p>Some papers were earlier shared on this discussion forum:<br>\n<a href=\"url\" target=\"_blank\">https://www.kaggle.com/competitions/stanford-ribonanza-rna-folding/discussion/437794</a></p>",
      "rawMarkdown": "I am citing here some of the relevant research papers for this competition:\n1. Marek Justyna, Maciej Antczak, Marta Szachniuk, Machine learning for RNA 2D structure prediction benchmarked on experimental data, Briefings in Bioinformatics, Volume 24, Issue 3, May 2023, bbad153, https://doi.org/10.1093/bib/bbad153\nlink: [https://academic.oup.com/bib/article/24/3/bbad153/7140288](url)\n2. Nicola Calonaci, et al.,  Machine learning a model for RNA structure prediction, NAR Genomics and Bioinformatics, Volume 2, Issue 4, December 2020, lqaa090, https://doi.org/10.1093/nargab/lqaa090\nlink: [https://academic.oup.com/nargab/article/2/4/lqaa090/5983421](url)\n3. Wang, Xunxun, et al.. \"RNA 3D Structure Prediction: Progress and Perspective\" Molecules 28, no. 14: 5532. https://doi.org/10.3390/molecules28145532\nlink: [https://www.mdpi.com/1420-3049/28/14/5532](url)\n4. Machine learning accurately predicts RNA structures using tiny dataset\nBY TOM METCALFE  7 SEPTEMBER 2021 link: [https://www.chemistryworld.com/news/machine-learning-accurately-predicts-rna-structures-using-tiny-dataset/4014347.article](url)\n5. Qi Zhao et al., Review of machine learning methods for RNA secondary structure prediction\nPublished: August 26, 2021\nhttps://doi.org/10.1371/journal.pcbi.1009291\nlink: [https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009291](url)\n\nSome papers were earlier shared on this discussion forum:\n[https://www.kaggle.com/competitions/stanford-ribonanza-rna-folding/discussion/437794](url)",
      "votes": 3
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "2506394": "I am citing here some of the relevant research papers for this competition:\n1. Marek Justyna, Maciej Antczak, Marta Szachniuk, Machine learning for RNA 2D structure prediction benchmarked on experimental data, Briefings in Bioinformatics, Volume 24, Issue 3, May 2023, bbad153, https://doi.org/10.1093/bib/bbad153\nlink: [https://academic.oup.com/bib/article/24/3/bbad153/7140288](url)\n2. Nicola Calonaci, et al.,  Machine learning a model for RNA structure prediction, NAR Genomics and Bioinformatics, Volume 2, Issue 4, December 2020, lqaa090, https://doi.org/10.1093/nargab/lqaa090\nlink: [https://academic.oup.com/nargab/article/2/4/lqaa090/5983421](url)\n3. Wang, Xunxun, et al.. \"RNA 3D Structure Prediction: Progress and Perspective\" Molecules 28, no. 14: 5532. https://doi.org/10.3390/molecules28145532\nlink: [https://www.mdpi.com/1420-3049/28/14/5532](url)\n4. Machine learning accurately predicts RNA structures using tiny dataset\nBY TOM METCALFE  7 SEPTEMBER 2021 link: [https://www.chemistryworld.com/news/machine-learning-accurately-predicts-rna-structures-using-tiny-dataset/4014347.article](url)\n5. Qi Zhao et al., Review of machine learning methods for RNA secondary structure prediction\nPublished: August 26, 2021\nhttps://doi.org/10.1371/journal.pcbi.1009291\nlink: [https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009291](url)\n\nSome papers were earlier shared on this discussion forum:\n[https://www.kaggle.com/competitions/stanford-ribonanza-rna-folding/discussion/437794](url)"
  }
}