{
  "id": 464178,
  "title": "Given reactivity values, how to infer RNA-structures?",
  "url": "/competitions/stanford-ribonanza-rna-folding/discussion/464178",
  "author_name": "",
  "post_date": "2023-12-29T04:26:10.535994100Z",
  "votes": null,
  "comment_count": 1,
  "views": 0,
  "content": "<p>Is there any algorithm that can derive RNA-structures based on the reactivity values (experiment/predicted) ? </p>",
  "messages": [
    {
      "id": "2578138",
      "postDate": "12/29/2023 04:26:10",
      "content": "<p>Is there any algorithm that can derive RNA-structures based on the reactivity values (experiment/predicted) ? </p>",
      "rawMarkdown": "Is there any algorithm that can derive RNA-structures based on the reactivity values (experiment/predicted) ?",
      "votes": null
    },
    {
      "id": "2579224",
      "postDate": "12/29/2023 23:03:19",
      "content": "<p>Yes, secondary structure can be inferred from the data, particularly if its possible to get data on mutants (sometimes called 'multidimensional chemical mapping'). A couple examples of using the reactivity values to guide ShapeKnots or a simple convnet called M2-net are in this <a href=\"https://www.pnas.org/doi/10.1073/pnas.1619897114\" target=\"_blank\">mutate-and-map paper</a>. There is less work on using predicted reactivity data to infer structure -- hopefully, this idea will be explored more widely as we publish the Ribonanza Kaggle models!</p>",
      "rawMarkdown": "Yes, secondary structure can be inferred from the data, particularly if its possible to get data on mutants (sometimes called 'multidimensional chemical mapping'). A couple examples of using the reactivity values to guide ShapeKnots or a simple convnet called M2-net are in this [mutate-and-map paper](https://www.pnas.org/doi/10.1073/pnas.1619897114). There is less work on using predicted reactivity data to infer structure -- hopefully, this idea will be explored more widely as we publish the Ribonanza Kaggle models!",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 2579224,
      "author_name": "rhijudas",
      "author_url": "",
      "post_date": "12/29/2023 23:03:19",
      "content": "<p>Yes, secondary structure can be inferred from the data, particularly if its possible to get data on mutants (sometimes called 'multidimensional chemical mapping'). A couple examples of using the reactivity values to guide ShapeKnots or a simple convnet called M2-net are in this <a href=\"https://www.pnas.org/doi/10.1073/pnas.1619897114\" target=\"_blank\">mutate-and-map paper</a>. There is less work on using predicted reactivity data to infer structure -- hopefully, this idea will be explored more widely as we publish the Ribonanza Kaggle models!</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "2578138": "Is there any algorithm that can derive RNA-structures based on the reactivity values (experiment/predicted) ?",
    "2579224": "Yes, secondary structure can be inferred from the data, particularly if its possible to get data on mutants (sometimes called 'multidimensional chemical mapping'). A couple examples of using the reactivity values to guide ShapeKnots or a simple convnet called M2-net are in this [mutate-and-map paper](https://www.pnas.org/doi/10.1073/pnas.1619897114). There is less work on using predicted reactivity data to infer structure -- hopefully, this idea will be explored more widely as we publish the Ribonanza Kaggle models!"
  },
  "source": "meta"
}