{
  "id": 668637,
  "title": "How can I learn about the domain for this challenge?",
  "url": "/competitions/stanford-rna-3d-folding-2/discussion/668637",
  "author_name": "SacredDeer",
  "post_date": "2026-01-18T02:58:46.815000",
  "votes": 4,
  "comment_count": 3,
  "views": 0,
  "content": "<p>Hi all,</p>\n<p>Does anyone have any tips on how I can learn the domain for this competition? I'm not a complete stranger to computational biology, and I plan to read the paper from Part 1 of the competition, but beyond that I don't know where exactly to look. Are there any papers from the Das Lab I should read? Anything else? Any advice would be great.</p>\n<p>Thank you so much!</p>",
  "messages": [
    {
      "id": 3415782,
      "postDate": "2026-03-01T10:05:22.013Z",
      "content": "<p>Great question! A few resources to get started:</p>\n<ul>\n<li><strong>Das Lab</strong>: Browse their <a href=\"https://daslab.stanford.edu/publications\" target=\"_blank\">publications</a>, especially <em>FARFAR2</em> (Watkins et al., 2020) for RNA 3D fragment assembly.</li>\n<li><strong>Deep learning models</strong>: <em>RoseTTAFold2NA</em> and <em>AlphaFold3</em> are the current state-of-the-art for RNA structure prediction.</li>\n<li><strong>Benchmarks</strong>: The <em>RNA-Puzzles</em> papers are great for understanding the field's progress and challenges.</li>\n</ul>\n<p>Good luck!</p>",
      "rawMarkdown": "Great question! A few resources to get started:\n\n- **Das Lab**: Browse their [publications](https://daslab.stanford.edu/publications), especially *FARFAR2* (Watkins et al., 2020) for RNA 3D fragment assembly.\n- **Deep learning models**: *RoseTTAFold2NA* and *AlphaFold3* are the current state-of-the-art for RNA structure prediction.\n- **Benchmarks**: The *RNA-Puzzles* papers are great for understanding the field's progress and challenges.\n\nGood luck!",
      "votes": 1
    },
    {
      "id": 3392988,
      "postDate": "2026-01-18T02:58:46.817Z",
      "content": "<p>Hi all,</p>\n<p>Does anyone have any tips on how I can learn the domain for this competition? I'm not a complete stranger to computational biology, and I plan to read the paper from Part 1 of the competition, but beyond that I don't know where exactly to look. Are there any papers from the Das Lab I should read? Anything else? Any advice would be great.</p>\n<p>Thank you so much!</p>",
      "rawMarkdown": "Hi all,\n\nDoes anyone have any tips on how I can learn the domain for this competition? I'm not a complete stranger to computational biology, and I plan to read the paper from Part 1 of the competition, but beyond that I don't know where exactly to look. Are there any papers from the Das Lab I should read? Anything else? Any advice would be great.\n\nThank you so much!",
      "votes": 4
    },
    {
      "id": 3395516,
      "postDate": "2026-01-23T05:24:37.497Z",
      "content": "<p><a href=\"https://pmc.ncbi.nlm.nih.gov/articles/PMC10199776/#ref32\" target=\"_blank\">https://pmc.ncbi.nlm.nih.gov/articles/PMC10199776/#ref32</a></p>\n<p>Read references and data set analysis provided. This may be helpful.</p>",
      "rawMarkdown": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10199776/#ref32\n\nRead references and data set analysis provided. This may be helpful.",
      "votes": 2,
      "replies": [
        {
          "id": 3397828,
          "postDate": "2026-01-28T05:30:17.493Z",
          "content": "<p>This is great, thank you!</p>",
          "rawMarkdown": "This is great, thank you!"
        }
      ]
    }
  ],
  "comments": [
    {
      "id": 3415782,
      "author_name": "Craig_Parker",
      "author_url": "",
      "post_date": "2026-03-01T10:05:22.013000",
      "content": "<p>Great question! A few resources to get started:</p>\n<ul>\n<li><strong>Das Lab</strong>: Browse their <a href=\"https://daslab.stanford.edu/publications\" target=\"_blank\">publications</a>, especially <em>FARFAR2</em> (Watkins et al., 2020) for RNA 3D fragment assembly.</li>\n<li><strong>Deep learning models</strong>: <em>RoseTTAFold2NA</em> and <em>AlphaFold3</em> are the current state-of-the-art for RNA structure prediction.</li>\n<li><strong>Benchmarks</strong>: The <em>RNA-Puzzles</em> papers are great for understanding the field's progress and challenges.</li>\n</ul>\n<p>Good luck!</p>",
      "votes": 1,
      "replies": []
    },
    {
      "id": 3395516,
      "author_name": "DILIP BAVISKAR",
      "author_url": "",
      "post_date": "2026-01-23T05:24:37.497000",
      "content": "<p><a href=\"https://pmc.ncbi.nlm.nih.gov/articles/PMC10199776/#ref32\" target=\"_blank\">https://pmc.ncbi.nlm.nih.gov/articles/PMC10199776/#ref32</a></p>\n<p>Read references and data set analysis provided. This may be helpful.</p>",
      "votes": 2,
      "replies": [
        {
          "id": 3397828,
          "author_name": "SacredDeer",
          "author_url": "",
          "post_date": "2026-01-28T05:30:17.493000",
          "content": "<p>This is great, thank you!</p>",
          "votes": 0,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "3415782": "Great question! A few resources to get started:\n\n- **Das Lab**: Browse their [publications](https://daslab.stanford.edu/publications), especially *FARFAR2* (Watkins et al., 2020) for RNA 3D fragment assembly.\n- **Deep learning models**: *RoseTTAFold2NA* and *AlphaFold3* are the current state-of-the-art for RNA structure prediction.\n- **Benchmarks**: The *RNA-Puzzles* papers are great for understanding the field's progress and challenges.\n\nGood luck!",
    "3392988": "Hi all,\n\nDoes anyone have any tips on how I can learn the domain for this competition? I'm not a complete stranger to computational biology, and I plan to read the paper from Part 1 of the competition, but beyond that I don't know where exactly to look. Are there any papers from the Das Lab I should read? Anything else? Any advice would be great.\n\nThank you so much!",
    "3395516": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10199776/#ref32\n\nRead references and data set analysis provided. This may be helpful."
  }
}