Hi, I’ve been on Kaggle for a bit, but this RNA 3D Folding competition is totally new territory for me. I’m not a beginner to Kaggle, but I am to this kind of challenge. I want to upskill and dive in—any simple advice on where to start or what to focus on? Like, what tools, skills, or resources should I pick up to tackle this RNA stuff? Would love some help from you all—keep it easy to follow, nothing too complicated!
", "messages": [ { "id": "3137995", "postDate": "03/02/2025 06:33:40", "content": "Hi, I’ve been on Kaggle for a bit, but this RNA 3D Folding competition is totally new territory for me. I’m not a beginner to Kaggle, but I am to this kind of challenge. I want to upskill and dive in—any simple advice on where to start or what to focus on? Like, what tools, skills, or resources should I pick up to tackle this RNA stuff? Would love some help from you all—keep it easy to follow, nothing too complicated!
", "rawMarkdown": "Hi, I’ve been on Kaggle for a bit, but this RNA 3D Folding competition is totally new territory for me. I’m not a beginner to Kaggle, but I am to this kind of challenge. I want to upskill and dive in—any simple advice on where to start or what to focus on? Like, what tools, skills, or resources should I pick up to tackle this RNA stuff? Would love some help from you all—keep it easy to follow, nothing too complicated!", "votes": null }, { "id": "3138027", "postDate": "03/02/2025 07:15:13", "content": "Hi, I’m in the same boat! I’ve been on Kaggle for a while, but this RNA 3D Folding competition is totally new to me too. I’d love some simple advice to get started….From what I’ve seen, learning the basics of RNA structure and using Python libraries like Biopython for data handling and PyMOL for visualization could help. Exploring graph-based methods or GNNs might also be useful since RNA can be represented as graphs.
\nAny tips or resources to make this less overwhelming would be amazing!!
", "rawMarkdown": "Hi, I’m in the same boat! I’ve been on Kaggle for a while, but this RNA 3D Folding competition is totally new to me too. I’d love some simple advice to get started....From what I’ve seen, learning the basics of RNA structure and using Python libraries like Biopython for data handling and PyMOL for visualization could help. Exploring graph-based methods or GNNs might also be useful since RNA can be represented as graphs. \n\nAny tips or resources to make this less overwhelming would be amazing!!", "votes": null }, { "id": "3140143", "postDate": "03/04/2025 10:23:58", "content": "Is it necessary to have domain specific knowledge??
", "rawMarkdown": "Is it necessary to have domain specific knowledge??", "votes": null }, { "id": "3141640", "postDate": "03/05/2025 20:15:05", "content": "Будьте терплячим, доброзичливим та зосередьтеся на ідеях. Ми всі тут аби навчатися чомусь новому та вдосконалювати вивчене.
", "rawMarkdown": "Будьте терплячим, доброзичливим та зосередьтеся на ідеях. Ми всі тут аби навчатися чомусь новому та вдосконалювати вивчене.", "votes": null }, { "id": "3157740", "postDate": "03/23/2025 18:56:55", "content": "Great to see you diving into this challenge! Since RNA 3D folding is bioinformatics-heavy, I'd recommend starting with:
\n🔹 Understanding RNA structure basics (YouTube & Coursera have great intros).
\n🔹 Learning about graph neural networks (GNNs) and their role in structural biology.
\n🔹 Exploring tools like RNAfold & ViennaRNA Package for simulations.
\n🔹 Checking past Kaggle competitions in structural biology for insights.
Start simple, experiment, and iterate! Excited to see how you progress!
", "rawMarkdown": "Great to see you diving into this challenge! Since RNA 3D folding is bioinformatics-heavy, I'd recommend starting with:\n\n🔹 Understanding RNA structure basics (YouTube & Coursera have great intros).\n🔹 Learning about graph neural networks (GNNs) and their role in structural biology.\n🔹 Exploring tools like RNAfold & ViennaRNA Package for simulations.\n🔹 Checking past Kaggle competitions in structural biology for insights.\n\nStart simple, experiment, and iterate! Excited to see how you progress!", "votes": null }, { "id": "3157913", "postDate": "03/24/2025 03:13:42", "content": "for machine learning, the best for newbie is COPY.
\njust find one repo that has EVERYTHING, training script, inference script, train data, pretrain model, etc …
\nthe best is that you don't have to write any code, can just run their code.
\nthen try to read the paper and DUPLICATE their RESULTS. I would say duplicating (and simplifiying etc. less layers) alphafold3 clone is a good choice.
this is becuase there are more vuideo, blog that explain how why it work, etc.
\nand ithink you also need to know alphafold2 (alphafold3 is modified of 2, 2 has more detailed implementation)
you may not get good ranking, but you will be VERY familiar with the topics, which will be greate advanage if similar competition comes next time
", "rawMarkdown": "for machine learning, the best for newbie is COPY.\njust find one repo that has EVERYTHING, training script, inference script, train data, pretrain model, etc ... \nthe best is that you don't have to write any code, can just run their code.\nthen try to read the paper and DUPLICATE their RESULTS. I would say duplicating (and simplifiying etc. less layers) alphafold3 clone is a good choice.\n\nthis is becuase there are more vuideo, blog that explain how why it work, etc.\nand ithink you also need to know alphafold2 (alphafold3 is modified of 2, 2 has more detailed implementation)\n\nyou may not get good ranking, but you will be VERY familiar with the topics, which will be greate advanage if similar competition comes next time", "votes": null }, { "id": "3158950", "postDate": "03/25/2025 04:52:30", "content": "To get started with the RNA 3D Folding competition, focus on understanding RNA structure and basic bioinformatics concepts like sequence folding. Use tools like Pandas and NumPy for data manipulation, Biopython for sequence analysis, and TensorFlow/PyTorch for deep learning models. Learn about feature engineering to convert sequences into usable data and familiarize yourself with visualization tools like PyMOL to analyze 3D structures. Focus on building models like CNNs or RNNs for structure prediction and stay comfortable with the data preprocessing process.
", "rawMarkdown": "To get started with the RNA 3D Folding competition, focus on understanding RNA structure and basic bioinformatics concepts like sequence folding. Use tools like Pandas and NumPy for data manipulation, Biopython for sequence analysis, and TensorFlow/PyTorch for deep learning models. Learn about feature engineering to convert sequences into usable data and familiarize yourself with visualization tools like PyMOL to analyze 3D structures. Focus on building models like CNNs or RNNs for structure prediction and stay comfortable with the data preprocessing process.", "votes": null } ], "comments": [ { "id": 3138027, "author_name": "ananya12verma", "author_url": "", "post_date": "03/02/2025 07:15:13", "content": "Hi, I’m in the same boat! I’ve been on Kaggle for a while, but this RNA 3D Folding competition is totally new to me too. I’d love some simple advice to get started….From what I’ve seen, learning the basics of RNA structure and using Python libraries like Biopython for data handling and PyMOL for visualization could help. Exploring graph-based methods or GNNs might also be useful since RNA can be represented as graphs.
\nAny tips or resources to make this less overwhelming would be amazing!!
", "votes": null, "replies": [ { "id": 3140143, "author_name": "anishnehete", "author_url": "", "post_date": "03/04/2025 10:23:58", "content": "Is it necessary to have domain specific knowledge??
", "votes": null, "replies": [] } ] }, { "id": 3141640, "author_name": "kravchukanna", "author_url": "", "post_date": "03/05/2025 20:15:05", "content": "Будьте терплячим, доброзичливим та зосередьтеся на ідеях. Ми всі тут аби навчатися чомусь новому та вдосконалювати вивчене.
", "votes": null, "replies": [] }, { "id": 3157740, "author_name": "wasifullahcs", "author_url": "", "post_date": "03/23/2025 18:56:55", "content": "Great to see you diving into this challenge! Since RNA 3D folding is bioinformatics-heavy, I'd recommend starting with:
\n🔹 Understanding RNA structure basics (YouTube & Coursera have great intros).
\n🔹 Learning about graph neural networks (GNNs) and their role in structural biology.
\n🔹 Exploring tools like RNAfold & ViennaRNA Package for simulations.
\n🔹 Checking past Kaggle competitions in structural biology for insights.
Start simple, experiment, and iterate! Excited to see how you progress!
", "votes": null, "replies": [] }, { "id": 3157913, "author_name": "hengck23", "author_url": "", "post_date": "03/24/2025 03:13:42", "content": "for machine learning, the best for newbie is COPY.
\njust find one repo that has EVERYTHING, training script, inference script, train data, pretrain model, etc …
\nthe best is that you don't have to write any code, can just run their code.
\nthen try to read the paper and DUPLICATE their RESULTS. I would say duplicating (and simplifiying etc. less layers) alphafold3 clone is a good choice.
this is becuase there are more vuideo, blog that explain how why it work, etc.
\nand ithink you also need to know alphafold2 (alphafold3 is modified of 2, 2 has more detailed implementation)
you may not get good ranking, but you will be VERY familiar with the topics, which will be greate advanage if similar competition comes next time
", "votes": null, "replies": [] }, { "id": 3158950, "author_name": "atharvasoundankar", "author_url": "", "post_date": "03/25/2025 04:52:30", "content": "To get started with the RNA 3D Folding competition, focus on understanding RNA structure and basic bioinformatics concepts like sequence folding. Use tools like Pandas and NumPy for data manipulation, Biopython for sequence analysis, and TensorFlow/PyTorch for deep learning models. Learn about feature engineering to convert sequences into usable data and familiarize yourself with visualization tools like PyMOL to analyze 3D structures. Focus on building models like CNNs or RNNs for structure prediction and stay comfortable with the data preprocessing process.
", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "3137995": "Hi, I’ve been on Kaggle for a bit, but this RNA 3D Folding competition is totally new territory for me. I’m not a beginner to Kaggle, but I am to this kind of challenge. I want to upskill and dive in—any simple advice on where to start or what to focus on? Like, what tools, skills, or resources should I pick up to tackle this RNA stuff? Would love some help from you all—keep it easy to follow, nothing too complicated!", "3138027": "Hi, I’m in the same boat! I’ve been on Kaggle for a while, but this RNA 3D Folding competition is totally new to me too. I’d love some simple advice to get started....From what I’ve seen, learning the basics of RNA structure and using Python libraries like Biopython for data handling and PyMOL for visualization could help. Exploring graph-based methods or GNNs might also be useful since RNA can be represented as graphs. \n\nAny tips or resources to make this less overwhelming would be amazing!!", "3140143": "Is it necessary to have domain specific knowledge??", "3141640": "Будьте терплячим, доброзичливим та зосередьтеся на ідеях. Ми всі тут аби навчатися чомусь новому та вдосконалювати вивчене.", "3157740": "Great to see you diving into this challenge! Since RNA 3D folding is bioinformatics-heavy, I'd recommend starting with:\n\n🔹 Understanding RNA structure basics (YouTube & Coursera have great intros).\n🔹 Learning about graph neural networks (GNNs) and their role in structural biology.\n🔹 Exploring tools like RNAfold & ViennaRNA Package for simulations.\n🔹 Checking past Kaggle competitions in structural biology for insights.\n\nStart simple, experiment, and iterate! Excited to see how you progress!", "3157913": "for machine learning, the best for newbie is COPY.\njust find one repo that has EVERYTHING, training script, inference script, train data, pretrain model, etc ... \nthe best is that you don't have to write any code, can just run their code.\nthen try to read the paper and DUPLICATE their RESULTS. I would say duplicating (and simplifiying etc. less layers) alphafold3 clone is a good choice.\n\nthis is becuase there are more vuideo, blog that explain how why it work, etc.\nand ithink you also need to know alphafold2 (alphafold3 is modified of 2, 2 has more detailed implementation)\n\nyou may not get good ranking, but you will be VERY familiar with the topics, which will be greate advanage if similar competition comes next time", "3158950": "To get started with the RNA 3D Folding competition, focus on understanding RNA structure and basic bioinformatics concepts like sequence folding. Use tools like Pandas and NumPy for data manipulation, Biopython for sequence analysis, and TensorFlow/PyTorch for deep learning models. Learn about feature engineering to convert sequences into usable data and familiarize yourself with visualization tools like PyMOL to analyze 3D structures. Focus on building models like CNNs or RNNs for structure prediction and stay comfortable with the data preprocessing process." }, "source": "meta" }