{ "id": 437766, "title": "Adjutant onboarding materials", "url": "/competitions/stanford-ribonanza-rna-folding/discussion/437766", "author_name": "", "post_date": "2023-09-08T05:20:40.201266800Z", "votes": 12, "comment_count": 3, "views": 0, "content": "

Hello all,

\n

Wishing you the best for the competition. Hope the below resources could be of use to one and all to onboard effectively-

\n

1. Competition - Open Problems - Multimodal Single-Cell Integration

\n

Overview - https://www.kaggle.com/competitions/open-problems-multimodal/overview

\n

Kernels

\n

a. https://www.kaggle.com/code/ambrosm/msci-eda-which-makes-sense
\nb. https://www.kaggle.com/code/ambrosm/msci-citeseq-quickstart
\nc. https://www.kaggle.com/code/pourchot/all-in-one-citeseq-multiome-with-keras
\nd. https://www.kaggle.com/code/fabiencrom/msci-multiome-quickstart-w-sparse-matrices

\n

Winner approaches

\n

a. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366961 -- rank1
\nb. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366453 -- rank2
\nc. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366428 -- rank3
\nd. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366460 -- rank4
\ne. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366409 -- rank5
\nf. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366417 -- rank6
\ng. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366471 -- rank7

\n

Other popular posts

\n

a. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/346888 -- domain elements
\nb. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/349867 -- discusses a leak
\nc. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/363052 -- discusses this as a time series assignment

\n

2. Competition - Novozymes Enzyme Stability Prediction

\n

Overview - https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction

\n

Kernels

\n

a. https://www.kaggle.com/code/dschettler8845/novo-esp-eli5-performant-approaches-lb-0-451
\nb. https://www.kaggle.com/code/cdeotte/xgboost-5000-mutations-200-pdb-files-lb-0-410
\nc. https://www.kaggle.com/code/seyered/eda-novozymes-enzyme-stability
\nd. https://www.kaggle.com/code/vslaykovsky/nesp-thermonet-v2
\ne. https://www.kaggle.com/code/cdeotte/difference-features-lb-0-600
\nf. https://www.kaggle.com/code/cdeotte/public-lb-1st-place-solution

\n

Winner approaches

\n

a. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/376371 -- rank1
\nb. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/376134 -- rank2
\nc. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/375964 -- rank3
\nd. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/375900 -- rank6
\ne. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/376070 -- rank8

\n

Other popular posts

\n

a. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/358320
\nb. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/376116 -- this could be of use here as the private LB is mentioned to be slightly different from the public LB to test model generalization. Please peruse the data page for details with emphasis on-
\nOur final and most important scoring (the Private Leaderboard) involves 1,031,888 sequences. Within this set, the majority (1,008,000 RNAs) will be experimentally synthesized and profiled after the Kaggle competition begins, to help ensure rigor. Furthermore, these test sequences will have lengths ranging from 207 to 457 bases -- we intentionally chose a different length distribution compared to the train data and Public Leaderboard, to help test the generality of your models
\nc. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/354806

\n

I shall update this with more relevant resources soon. All the best and happy learning!

", "messages": [ { "id": "2428690", "postDate": "09/08/2023 05:20:40", "content": "

Hello all,

\n

Wishing you the best for the competition. Hope the below resources could be of use to one and all to onboard effectively-

\n

1. Competition - Open Problems - Multimodal Single-Cell Integration

\n

Overview - https://www.kaggle.com/competitions/open-problems-multimodal/overview

\n

Kernels

\n

a. https://www.kaggle.com/code/ambrosm/msci-eda-which-makes-sense
\nb. https://www.kaggle.com/code/ambrosm/msci-citeseq-quickstart
\nc. https://www.kaggle.com/code/pourchot/all-in-one-citeseq-multiome-with-keras
\nd. https://www.kaggle.com/code/fabiencrom/msci-multiome-quickstart-w-sparse-matrices

\n

Winner approaches

\n

a. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366961 -- rank1
\nb. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366453 -- rank2
\nc. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366428 -- rank3
\nd. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366460 -- rank4
\ne. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366409 -- rank5
\nf. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366417 -- rank6
\ng. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366471 -- rank7

\n

Other popular posts

\n

a. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/346888 -- domain elements
\nb. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/349867 -- discusses a leak
\nc. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/363052 -- discusses this as a time series assignment

\n

2. Competition - Novozymes Enzyme Stability Prediction

\n

Overview - https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction

\n

Kernels

\n

a. https://www.kaggle.com/code/dschettler8845/novo-esp-eli5-performant-approaches-lb-0-451
\nb. https://www.kaggle.com/code/cdeotte/xgboost-5000-mutations-200-pdb-files-lb-0-410
\nc. https://www.kaggle.com/code/seyered/eda-novozymes-enzyme-stability
\nd. https://www.kaggle.com/code/vslaykovsky/nesp-thermonet-v2
\ne. https://www.kaggle.com/code/cdeotte/difference-features-lb-0-600
\nf. https://www.kaggle.com/code/cdeotte/public-lb-1st-place-solution

\n

Winner approaches

\n

a. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/376371 -- rank1
\nb. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/376134 -- rank2
\nc. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/375964 -- rank3
\nd. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/375900 -- rank6
\ne. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/376070 -- rank8

\n

Other popular posts

\n

a. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/358320
\nb. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/376116 -- this could be of use here as the private LB is mentioned to be slightly different from the public LB to test model generalization. Please peruse the data page for details with emphasis on-
\nOur final and most important scoring (the Private Leaderboard) involves 1,031,888 sequences. Within this set, the majority (1,008,000 RNAs) will be experimentally synthesized and profiled after the Kaggle competition begins, to help ensure rigor. Furthermore, these test sequences will have lengths ranging from 207 to 457 bases -- we intentionally chose a different length distribution compared to the train data and Public Leaderboard, to help test the generality of your models
\nc. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/354806

\n

I shall update this with more relevant resources soon. All the best and happy learning!

", "rawMarkdown": "Hello all, \n\nWishing you the best for the competition. Hope the below resources could be of use to one and all to onboard effectively- \n\n## 1. **Competition - Open Problems - Multimodal Single-Cell Integration** \n### **Overview** - https://www.kaggle.com/competitions/open-problems-multimodal/overview\n### **Kernels**
\na. https://www.kaggle.com/code/ambrosm/msci-eda-which-makes-sense \nb. https://www.kaggle.com/code/ambrosm/msci-citeseq-quickstart\nc. https://www.kaggle.com/code/pourchot/all-in-one-citeseq-multiome-with-keras \nd. https://www.kaggle.com/code/fabiencrom/msci-multiome-quickstart-w-sparse-matrices \n### **Winner approaches**
\na. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366961 -- rank1 \nb. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366453 -- rank2 \nc. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366428 -- rank3 \nd. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366460 -- rank4 \ne. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366409 -- rank5 \nf. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366417 -- rank6 \ng. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366471 -- rank7 \n### **Other popular posts**\na. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/346888 -- domain elements \nb. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/349867 -- discusses a leak \nc. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/363052 -- discusses this as a time series assignment\n\n## 2. **Competition - Novozymes Enzyme Stability Prediction** \n### **Overview** - https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction \n### **Kernels** \na. https://www.kaggle.com/code/dschettler8845/novo-esp-eli5-performant-approaches-lb-0-451\nb. https://www.kaggle.com/code/cdeotte/xgboost-5000-mutations-200-pdb-files-lb-0-410 \nc. https://www.kaggle.com/code/seyered/eda-novozymes-enzyme-stability\nd. https://www.kaggle.com/code/vslaykovsky/nesp-thermonet-v2\ne. https://www.kaggle.com/code/cdeotte/difference-features-lb-0-600\nf. https://www.kaggle.com/code/cdeotte/public-lb-1st-place-solution \n### **Winner approaches**\na. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/376371 -- rank1\nb. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/376134 -- rank2 \nc. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/375964 -- rank3 \nd. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/375900 -- rank6 \ne. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/376070 -- rank8 \n### **Other popular posts** \na. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/358320 \nb. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/376116 -- this could be of use here as the private LB is mentioned to be slightly different from the public LB to test model generalization. Please peruse the [data page](https://www.kaggle.com/competitions/stanford-ribonanza-rna-folding/data) for details with emphasis on- \n**Our final and most important scoring (the Private Leaderboard) involves 1,031,888 sequences. Within this set, the majority (1,008,000 RNAs) will be experimentally synthesized and profiled after the Kaggle competition begins, to help ensure rigor. Furthermore, these test sequences will have lengths ranging from 207 to 457 bases -- we intentionally chose a different length distribution compared to the train data and Public Leaderboard, to help test the generality of your models**\nc. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/354806\n\nI shall update this with more relevant resources soon. All the best and happy learning!", "votes": null }, { "id": "2428712", "postDate": "09/08/2023 05:30:19", "content": "

Thanks for sharing @ravi20076. This will definitely help.

", "rawMarkdown": "Thanks for sharing @ravi20076. This will definitely help.", "votes": null }, { "id": "2435723", "postDate": "09/13/2023 06:26:23", "content": "

thanks for sharing. 👏

", "rawMarkdown": "thanks for sharing. 👏", "votes": null }, { "id": "2455616", "postDate": "09/25/2023 15:48:50", "content": "

Thanks for sharing ! it is helpful

", "rawMarkdown": "Thanks for sharing ! it is helpful", "votes": null } ], "comments": [ { "id": 2428712, "author_name": "rishabh15virgo", "author_url": "", "post_date": "09/08/2023 05:30:19", "content": "

Thanks for sharing @ravi20076. This will definitely help.

", "votes": null, "replies": [] }, { "id": 2435723, "author_name": "mehmetisik", "author_url": "", "post_date": "09/13/2023 06:26:23", "content": "

thanks for sharing. 👏

", "votes": null, "replies": [] }, { "id": 2455616, "author_name": "sahityasetu", "author_url": "", "post_date": "09/25/2023 15:48:50", "content": "

Thanks for sharing ! it is helpful

", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "2428690": "Hello all, \n\nWishing you the best for the competition. Hope the below resources could be of use to one and all to onboard effectively- \n\n## 1. **Competition - Open Problems - Multimodal Single-Cell Integration** \n### **Overview** - https://www.kaggle.com/competitions/open-problems-multimodal/overview\n### **Kernels**
\na. https://www.kaggle.com/code/ambrosm/msci-eda-which-makes-sense \nb. https://www.kaggle.com/code/ambrosm/msci-citeseq-quickstart\nc. https://www.kaggle.com/code/pourchot/all-in-one-citeseq-multiome-with-keras \nd. https://www.kaggle.com/code/fabiencrom/msci-multiome-quickstart-w-sparse-matrices \n### **Winner approaches**
\na. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366961 -- rank1 \nb. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366453 -- rank2 \nc. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366428 -- rank3 \nd. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366460 -- rank4 \ne. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366409 -- rank5 \nf. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366417 -- rank6 \ng. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/366471 -- rank7 \n### **Other popular posts**\na. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/346888 -- domain elements \nb. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/349867 -- discusses a leak \nc. https://www.kaggle.com/competitions/open-problems-multimodal/discussion/363052 -- discusses this as a time series assignment\n\n## 2. **Competition - Novozymes Enzyme Stability Prediction** \n### **Overview** - https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction \n### **Kernels** \na. https://www.kaggle.com/code/dschettler8845/novo-esp-eli5-performant-approaches-lb-0-451\nb. https://www.kaggle.com/code/cdeotte/xgboost-5000-mutations-200-pdb-files-lb-0-410 \nc. https://www.kaggle.com/code/seyered/eda-novozymes-enzyme-stability\nd. https://www.kaggle.com/code/vslaykovsky/nesp-thermonet-v2\ne. https://www.kaggle.com/code/cdeotte/difference-features-lb-0-600\nf. https://www.kaggle.com/code/cdeotte/public-lb-1st-place-solution \n### **Winner approaches**\na. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/376371 -- rank1\nb. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/376134 -- rank2 \nc. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/375964 -- rank3 \nd. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/375900 -- rank6 \ne. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/376070 -- rank8 \n### **Other popular posts** \na. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/358320 \nb. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/376116 -- this could be of use here as the private LB is mentioned to be slightly different from the public LB to test model generalization. Please peruse the [data page](https://www.kaggle.com/competitions/stanford-ribonanza-rna-folding/data) for details with emphasis on- \n**Our final and most important scoring (the Private Leaderboard) involves 1,031,888 sequences. Within this set, the majority (1,008,000 RNAs) will be experimentally synthesized and profiled after the Kaggle competition begins, to help ensure rigor. Furthermore, these test sequences will have lengths ranging from 207 to 457 bases -- we intentionally chose a different length distribution compared to the train data and Public Leaderboard, to help test the generality of your models**\nc. https://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/354806\n\nI shall update this with more relevant resources soon. All the best and happy learning!", "2428712": "Thanks for sharing @ravi20076. This will definitely help.", "2435723": "thanks for sharing. 👏", "2455616": "Thanks for sharing ! it is helpful" }, "source": "meta" }