Detailed description of the experiment
\n\"CASP (Critical Assessment of Structure Prediction) is a community wide experiment to determine and advance the state of the art in modeling protein structure from amino acid sequence. Every two years, participants are invited to submit models for a set of proteins for which the experimental structures are not yet public. Independent assessors then compare the models with experiment. Assessments and results are published in a special issue of the journal PROTEINS.\"
\nhttps://predictioncenter.org/casp15/index.cgi
\nhttps://predictioncenter.org/index.cgi?page=proceedings
\nApplying and improving AlphaFold at CASP14
\nCitation:
\nJohn Jumper, Richard Evans, Alexander Pritzel, Tim Green, Michael Figurnov, Olaf Ronneberger, Kathryn Tunyasuvunakool, Russ Bates, Augustin Žídek, Anna Potapenko, Alex Bridgland, Clemens Meyer, Simon A. A. Kohl, Andrew J. Ballard, Andrew Cowie, Bernardino Romera-Paredes, Stanislav Nikolov, Rishub Jain, and Demis Hassabis contributed equally.
\nFirst published: 02 October 2021 https://doi.org/10.1002/prot.26257
\"The authors described the operation and improvement of AlphaFold, the system that was entered by the team AlphaFold2 to the “human” category in the 14th Critical Assessment of Protein Structure Prediction (CASP14). The AlphaFold system entered in CASP14 is entirely different to the one entered in CASP13. It used a novel end-to-end deep neural network trained to produce protein structures from amino acid sequence, multiple sequence alignments, and homologous proteins. In the assessors' ranking by summed z scores (>2.0), AlphaFold scored 244.0 compared to 90.8 by the next best group. The predictions made by AlphaFold had a median domain GDT_TS of 92.4; this is the first time that this level of average accuracy has been achieved during CASP, especially on the more difficult Free Modeling targets, and represents a significant improvement in the state of the art in protein structure prediction. \"
\n\"The authors reported how AlphaFold was run as a human team during CASP14 and improved such that it now achieves an equivalent level of performance without intervention, opening the door to highly accurate large-scale structure prediction.\"
\nhttps://onlinelibrary.wiley.com/doi/abs/10.1002/prot.26257
\nArt gallery: Protein embeddings By Alexander Chervov
\nhttps://www.kaggle.com/competitions/cafa-5-protein-function-prediction/discussion/406658
CAFA5 Levenshtein distances feature visualizations - By Alexander Chervov
\nhttps://www.kaggle.com/code/alexandervc/cafa5-levenshtein-distances-feature-visualizations?scriptVersionId=127921968&cellId=13
KAGGLE COMPETITIONS
\nKaggle Competition: CAFA 5 Protein Function Prediction
\nhttps://www.kaggle.com/competitions/cafa-5-protein-function-prediction/discussion?sort=published&page=3
Kaggle Competition: Novozymes Enzyme Stability Prediction
\nhttps://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction
Kaggle Competition: Open Problems - Multimodal Single-Cell Integration
\nhttps://www.kaggle.com/competitions/open-problems-multimodal
Display Test Protein Using AlphaFold v2.1.0 By Chris Deotte
\nhttps://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/354982
AlphaFold, ColabFold, ESMFold, OmegaFold? … or DALL-E-fold? By HengCK23
\nhttps://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/356799
Is any part of ESMFold better than AlphaFold? By Tilll (tilli7)
\nhttps://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/364127
ESMFold API available - By Dieter
\nhttps://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/363651
AlphaFold and mutation - By CPMP
\nhttps://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/364592
AlphaFold Protein Structure Database: https://alphafold.ebi.ac.uk/
\nDetailed description of the experiment
\n\"CASP (Critical Assessment of Structure Prediction) is a community wide experiment to determine and advance the state of the art in modeling protein structure from amino acid sequence. Every two years, participants are invited to submit models for a set of proteins for which the experimental structures are not yet public. Independent assessors then compare the models with experiment. Assessments and results are published in a special issue of the journal PROTEINS.\"
\nhttps://predictioncenter.org/casp15/index.cgi
\nhttps://predictioncenter.org/index.cgi?page=proceedings
\nApplying and improving AlphaFold at CASP14
\nCitation:
\nJohn Jumper, Richard Evans, Alexander Pritzel, Tim Green, Michael Figurnov, Olaf Ronneberger, Kathryn Tunyasuvunakool, Russ Bates, Augustin Žídek, Anna Potapenko, Alex Bridgland, Clemens Meyer, Simon A. A. Kohl, Andrew J. Ballard, Andrew Cowie, Bernardino Romera-Paredes, Stanislav Nikolov, Rishub Jain, and Demis Hassabis contributed equally.
\nFirst published: 02 October 2021 https://doi.org/10.1002/prot.26257
\"The authors described the operation and improvement of AlphaFold, the system that was entered by the team AlphaFold2 to the “human” category in the 14th Critical Assessment of Protein Structure Prediction (CASP14). The AlphaFold system entered in CASP14 is entirely different to the one entered in CASP13. It used a novel end-to-end deep neural network trained to produce protein structures from amino acid sequence, multiple sequence alignments, and homologous proteins. In the assessors' ranking by summed z scores (>2.0), AlphaFold scored 244.0 compared to 90.8 by the next best group. The predictions made by AlphaFold had a median domain GDT_TS of 92.4; this is the first time that this level of average accuracy has been achieved during CASP, especially on the more difficult Free Modeling targets, and represents a significant improvement in the state of the art in protein structure prediction. \"
\n\"The authors reported how AlphaFold was run as a human team during CASP14 and improved such that it now achieves an equivalent level of performance without intervention, opening the door to highly accurate large-scale structure prediction.\"
\nhttps://onlinelibrary.wiley.com/doi/abs/10.1002/prot.26257
\nArt gallery: Protein embeddings By Alexander Chervov
\nhttps://www.kaggle.com/competitions/cafa-5-protein-function-prediction/discussion/406658
CAFA5 Levenshtein distances feature visualizations - By Alexander Chervov
\nhttps://www.kaggle.com/code/alexandervc/cafa5-levenshtein-distances-feature-visualizations?scriptVersionId=127921968&cellId=13
KAGGLE COMPETITIONS
\nKaggle Competition: CAFA 5 Protein Function Prediction
\nhttps://www.kaggle.com/competitions/cafa-5-protein-function-prediction/discussion?sort=published&page=3
Kaggle Competition: Novozymes Enzyme Stability Prediction
\nhttps://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction
Kaggle Competition: Open Problems - Multimodal Single-Cell Integration
\nhttps://www.kaggle.com/competitions/open-problems-multimodal
Display Test Protein Using AlphaFold v2.1.0 By Chris Deotte
\nhttps://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/354982
AlphaFold, ColabFold, ESMFold, OmegaFold? … or DALL-E-fold? By HengCK23
\nhttps://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/356799
Is any part of ESMFold better than AlphaFold? By Tilll (tilli7)
\nhttps://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/364127
ESMFold API available - By Dieter
\nhttps://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/363651
AlphaFold and mutation - By CPMP
\nhttps://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/364592
AlphaFold Protein Structure Database: https://alphafold.ebi.ac.uk/
\nWow that is so great!
", "rawMarkdown": "Wow that is so great!", "votes": 19 }, { "id": 2435729, "postDate": "2023-09-13T06:28:22.633Z", "content": "it is a good article. amazing👏
", "rawMarkdown": "it is a good article. amazing👏", "votes": 1 }, { "id": 2432259, "postDate": "2023-09-10T17:36:46.813Z", "content": "That was a good article to read. I've worked with proteins as a Bioinformatician before joining kaggle.. infact that was one of my major motivations to join the forum. Before reading it, I didn't know kaggle has hosted this much protein related competitions..
", "rawMarkdown": "That was a good article to read. I've worked with proteins as a Bioinformatician before joining kaggle.. infact that was one of my major motivations to join the forum. Before reading it, I didn't know kaggle has hosted this much protein related competitions..", "votes": 1, "replies": [ { "id": 2432496, "postDate": "2023-09-10T22:25:47.950Z", "content": "Indeed Rida, recently Kaggle brought those compelling Bioinformatics competitions.
\nCheck this topic by Alexander Chervov (bioinformatician too) with many Sources/links where we are able to learn about this subject on Kaggle.
\nhttps://www.kaggle.com/discussions/general/203136
Thanks for sharing! Just a little curious, How do you get so fast in every competition? Every time there is a new competition, I always immediately see a brief survey from you or some familiar faces. You guys probably do not have expertise in every single field there is. How do you manage to keep track of all these related works?
", "rawMarkdown": "Thanks for sharing! Just a little curious, How do you get so fast in every competition? Every time there is a new competition, I always immediately see a brief survey from you or some familiar faces. You guys probably do not have expertise in every single field there is. How do you manage to keep track of all these related works?", "votes": 2, "replies": [ { "id": 2428558, "postDate": "2023-09-08T02:26:55.393Z", "content": "Check it daily. By clicking on Competitions.
\nIn fact, I don't have any expertise at all. Not in programming nor on the subjects/fields too. Though learning about the data it's very motivating. Getting in touch with new material is compelling.
\nIf I publish later, no one will read what I've done. That's why I try to deliver public work as soon as I can.
\nIn Brazil, in general Timezone when competitions are launched is at night ( Now it's 23:17 in Brazil)
\nThis competition started 6 hours ago. Vietnam has 7 hours in difference?? Calculate what time it has started on your country.
Thanks for your reply. I think my phrasing of the question made you misunderstand it. By being fast, I meant how you compile the survey in just a short amount of time. That's why I mentioned expertise in each field. I'm just a junior researcher, so I always wonder how experienced people like you can come up with those literature reviews so quickly without knowing anything about them in advance.
", "rawMarkdown": "Thanks for your reply. I think my phrasing of the question made you misunderstand it. By being fast, I meant how you compile the survey in just a short amount of time. That's why I mentioned expertise in each field. I'm just a junior researcher, so I always wonder how experienced people like you can come up with those literature reviews so quickly without knowing anything about them in advance.", "votes": 1 }, { "id": 2429456, "postDate": "2023-09-08T15:58:31.410Z", "content": "Hi Nguyen,
\nI read the competition's instructions to get my inspiration to search like that:
metrics, the columns, files and folders ( to write about something New).
\nThe links the host selected (e.g. RFAM database, Kaggle Open Vaccine). Or expressions like \"mutational profiling (MaP) experiment.
I check also the Competition citation. For the record, only now I read the EteRNA players.
\nOn this challenge hosts provided Additional Resources. I click on those Resources to see if I can deliver something DIFFERENT, something related to those resources.
\nThis time, I read CASP, then I searched what is CASP15 ( it means Critical Assessment of Structure Prediction 15th 0n 2022). I found out many previous CASPs.
\nhttps://predictioncenter.org/casp15/index.cgi
When I opened the CASP15(2022), I read that (on Detailed description of the experiment) :
\n\"Assessments and results are published in a special issue of the JOURNAL PROTEINS (check the latest CASP14 issue here).\" That's how I arrived on Wiley Library (1st time there)
\nhttps://onlinelibrary.wiley.com/toc/10970134/2021/89/12
So, I checked that Journal PROTEINS, pick one article that called my attention:
\n\"Applying and improving AlphaFold at CASP14\" Because I've already seen many topics on Kaggle about AlphaFold.
This way was easy to connect a Paper (that I chose) to a Subject that many Kagglers had already written about on previous competitions.
\nWhat I try to deliver are explanations about things that the majority of beginners don't know. Then illustrate with the paper's Abstract/Conclusion (edit it as possible) providing citations/credits.
\nAdditionally, I include Kagglers relevant topics related to that subject.
\nOf course, it helps having participated on those competitions and reading public material (code and topics), so that it will be easier to find exactly what I want to focus and publish.
\nI always try to bring DIFFERENT and NEW material to those topics.
\nI hope I could have clarified it. You're welcome to ask anything further.
", "rawMarkdown": "Hi Nguyen,\nI read the competition's instructions to get my inspiration to search like that: \n\nmetrics, the columns, files and folders ( to write about something New). \nThe links the host selected (e.g. RFAM database, Kaggle Open Vaccine). Or expressions like \"mutational profiling (MaP) experiment.\n\nI check also the Competition citation. For the record, only now I read the EteRNA players.\n\nOn this challenge hosts provided Additional Resources. I click on those Resources to see if I can deliver something DIFFERENT, something related to those resources.\n\nThis time, I read CASP, then I searched what is CASP15 ( it means Critical Assessment of Structure Prediction 15th 0n 2022). I found out many previous CASPs. \nhttps://predictioncenter.org/casp15/index.cgi\n\n When I opened the CASP15(2022), I read that (on Detailed description of the experiment) :\n\"Assessments and results are published in a special issue of the JOURNAL PROTEINS (check the latest CASP14 issue here).\" That's how I arrived on Wiley Library (1st time there)\nhttps://onlinelibrary.wiley.com/toc/10970134/2021/89/12\n\nSo, I checked that Journal PROTEINS, pick one article that called my attention:\n\"Applying and improving AlphaFold at CASP14\" Because I've already seen many topics on Kaggle about AlphaFold.\n\nThis way was easy to connect a Paper (that I chose) to a Subject that many Kagglers had already written about on previous competitions. \n\nWhat I try to deliver are explanations about things that the majority of beginners don't know. Then illustrate with the paper's Abstract/Conclusion (edit it as possible) providing citations/credits.\n\nAdditionally, I include Kagglers relevant topics related to that subject.\n\nOf course, it helps having participated on those competitions and reading public material (code and topics), so that it will be easier to find exactly what I want to focus and publish.\n\nI always try to bring DIFFERENT and NEW material to those topics.\n\nI hope I could have clarified it. You're welcome to ask anything further. ", "votes": 5 }, { "id": 2430581, "postDate": "2023-09-09T11:29:18.580Z", "content": "Wow that is so detailed! Thanks so much for explaining your whole process. This should help me a lot in my next path.
", "rawMarkdown": "Wow that is so detailed! Thanks so much for explaining your whole process. This should help me a lot in my next path.", "votes": 1 } ] } ] }, { "id": 2428595, "postDate": "2023-09-08T03:23:36.967Z", "rawMarkdown": "", "votes": 5, "isDeleted": true, "replies": [ { "id": 2429468, "postDate": "2023-09-08T16:05:29.683Z", "content": "Thank you Nihilisticneuralnet also for your helpful Notebook with dask/chunk to read the csv files.
", "rawMarkdown": "Thank you Nihilisticneuralnet also for your helpful Notebook with dask/chunk to read the csv files." } ] }, { "id": 2441943, "postDate": "2023-09-16T15:14:44.497Z", "content": "Amazing article, thanks for sharing!
", "rawMarkdown": "Amazing article, thanks for sharing!", "votes": 1 }, { "id": 2438228, "postDate": "2023-09-14T06:20:23.570Z", "content": "useful,thanks
", "rawMarkdown": "useful,thanks\n", "votes": 1 } ], "comments": [ { "id": 2433472, "author_name": "Serhii Kharchuk", "author_url": "", "post_date": "2023-09-11T15:48:46.057000", "content": "Wow that is so great!
", "votes": 19, "replies": [] }, { "id": 2435729, "author_name": "Mehmet ISIK", "author_url": "", "post_date": "2023-09-13T06:28:22.633000", "content": "it is a good article. amazing👏
", "votes": 1, "replies": [] }, { "id": 2432259, "author_name": "Rida Mahmood", "author_url": "", "post_date": "2023-09-10T17:36:46.813000", "content": "That was a good article to read. I've worked with proteins as a Bioinformatician before joining kaggle.. infact that was one of my major motivations to join the forum. Before reading it, I didn't know kaggle has hosted this much protein related competitions..
", "votes": 1, "replies": [ { "id": 2432496, "author_name": "Marília Prata", "author_url": "", "post_date": "2023-09-10T22:25:47.950000", "content": "Indeed Rida, recently Kaggle brought those compelling Bioinformatics competitions.
\nCheck this topic by Alexander Chervov (bioinformatician too) with many Sources/links where we are able to learn about this subject on Kaggle.
\nhttps://www.kaggle.com/discussions/general/203136
Thanks for sharing! Just a little curious, How do you get so fast in every competition? Every time there is a new competition, I always immediately see a brief survey from you or some familiar faces. You guys probably do not have expertise in every single field there is. How do you manage to keep track of all these related works?
", "votes": 2, "replies": [ { "id": 2428558, "author_name": "Marília Prata", "author_url": "", "post_date": "2023-09-08T02:26:55.393000", "content": "Check it daily. By clicking on Competitions.
\nIn fact, I don't have any expertise at all. Not in programming nor on the subjects/fields too. Though learning about the data it's very motivating. Getting in touch with new material is compelling.
\nIf I publish later, no one will read what I've done. That's why I try to deliver public work as soon as I can.
\nIn Brazil, in general Timezone when competitions are launched is at night ( Now it's 23:17 in Brazil)
\nThis competition started 6 hours ago. Vietnam has 7 hours in difference?? Calculate what time it has started on your country.
Thanks for your reply. I think my phrasing of the question made you misunderstand it. By being fast, I meant how you compile the survey in just a short amount of time. That's why I mentioned expertise in each field. I'm just a junior researcher, so I always wonder how experienced people like you can come up with those literature reviews so quickly without knowing anything about them in advance.
", "votes": 1, "replies": [] }, { "id": 2429456, "author_name": "Marília Prata", "author_url": "", "post_date": "2023-09-08T15:58:31.410000", "content": "Hi Nguyen,
\nI read the competition's instructions to get my inspiration to search like that:
metrics, the columns, files and folders ( to write about something New).
\nThe links the host selected (e.g. RFAM database, Kaggle Open Vaccine). Or expressions like \"mutational profiling (MaP) experiment.
I check also the Competition citation. For the record, only now I read the EteRNA players.
\nOn this challenge hosts provided Additional Resources. I click on those Resources to see if I can deliver something DIFFERENT, something related to those resources.
\nThis time, I read CASP, then I searched what is CASP15 ( it means Critical Assessment of Structure Prediction 15th 0n 2022). I found out many previous CASPs.
\nhttps://predictioncenter.org/casp15/index.cgi
When I opened the CASP15(2022), I read that (on Detailed description of the experiment) :
\n\"Assessments and results are published in a special issue of the JOURNAL PROTEINS (check the latest CASP14 issue here).\" That's how I arrived on Wiley Library (1st time there)
\nhttps://onlinelibrary.wiley.com/toc/10970134/2021/89/12
So, I checked that Journal PROTEINS, pick one article that called my attention:
\n\"Applying and improving AlphaFold at CASP14\" Because I've already seen many topics on Kaggle about AlphaFold.
This way was easy to connect a Paper (that I chose) to a Subject that many Kagglers had already written about on previous competitions.
\nWhat I try to deliver are explanations about things that the majority of beginners don't know. Then illustrate with the paper's Abstract/Conclusion (edit it as possible) providing citations/credits.
\nAdditionally, I include Kagglers relevant topics related to that subject.
\nOf course, it helps having participated on those competitions and reading public material (code and topics), so that it will be easier to find exactly what I want to focus and publish.
\nI always try to bring DIFFERENT and NEW material to those topics.
\nI hope I could have clarified it. You're welcome to ask anything further.
", "votes": 5, "replies": [] }, { "id": 2430581, "author_name": "mp", "author_url": "", "post_date": "2023-09-09T11:29:18.580000", "content": "Wow that is so detailed! Thanks so much for explaining your whole process. This should help me a lot in my next path.
", "votes": 1, "replies": [] } ] } ] }, { "id": 2428595, "author_name": "", "author_url": "", "post_date": "2023-09-08T03:23:36.967000", "content": "", "votes": 5, "replies": [ { "id": 2429468, "author_name": "Marília Prata", "author_url": "", "post_date": "2023-09-08T16:05:29.683000", "content": "Thank you Nihilisticneuralnet also for your helpful Notebook with dask/chunk to read the csv files.
", "votes": 0, "replies": [] } ] }, { "id": 2441943, "author_name": "bai2ertwo", "author_url": "", "post_date": "2023-09-16T15:14:44.497000", "content": "Amazing article, thanks for sharing!
", "votes": 1, "replies": [] }, { "id": 2438228, "author_name": "nini_good", "author_url": "", "post_date": "2023-09-14T06:20:23.570000", "content": "useful,thanks
", "votes": 1, "replies": [] } ], "raw_markdown_by_id": { "2428501": "#CASP (Critical Assessment of Structure Prediction)\n\nDetailed description of the experiment\n\n\"CASP (Critical Assessment of Structure Prediction) is a community wide experiment to determine and advance the state of the art in modeling protein structure from amino acid sequence. Every two years, participants are invited to submit models for a set of proteins for which the experimental structures are not yet public. Independent assessors then compare the models with experiment. Assessments and results are published in a special issue of the journal PROTEINS.\"\n\nhttps://predictioncenter.org/casp15/index.cgi\n\n#Protein Structure Prediction Center\nhttps://predictioncenter.org/index.cgi?page=proceedings\n\nApplying and improving AlphaFold at CASP14\n\nCitation: \nJohn Jumper, Richard Evans, Alexander Pritzel, Tim Green, Michael Figurnov, Olaf Ronneberger, Kathryn Tunyasuvunakool, Russ Bates, Augustin Žídek, Anna Potapenko, Alex Bridgland, Clemens Meyer, Simon A. A. Kohl, Andrew J. Ballard, Andrew Cowie, Bernardino Romera-Paredes, Stanislav Nikolov, Rishub Jain, and Demis Hassabis contributed equally.\nFirst published: 02 October 2021 https://doi.org/10.1002/prot.26257\n\n\"The authors described the operation and improvement of AlphaFold, the system that was entered by the team AlphaFold2 to the “human” category in the 14th Critical Assessment of Protein Structure Prediction (CASP14). The AlphaFold system entered in CASP14 is entirely different to the one entered in CASP13. It used a novel end-to-end deep neural network trained to produce protein structures from amino acid sequence, multiple sequence alignments, and homologous proteins. In the assessors' ranking by summed z scores (>2.0), AlphaFold scored 244.0 compared to 90.8 by the next best group. The predictions made by AlphaFold had a median domain GDT_TS of 92.4; this is the first time that this level of average accuracy has been achieved during CASP, especially on the more difficult Free Modeling targets, and represents a significant improvement in the state of the art in protein structure prediction. \"\n\n\"The authors reported how AlphaFold was run as a human team during CASP14 and improved such that it now achieves an equivalent level of performance without intervention, opening the door to highly accurate large-scale structure prediction.\"\n\nhttps://onlinelibrary.wiley.com/doi/abs/10.1002/prot.26257\n\n#Protein Prediction on Kaggle\n\nArt gallery: Protein embeddings By Alexander Chervov\nhttps://www.kaggle.com/competitions/cafa-5-protein-function-prediction/discussion/406658\n\nCAFA5 Levenshtein distances feature visualizations - By Alexander Chervov\nhttps://www.kaggle.com/code/alexandervc/cafa5-levenshtein-distances-feature-visualizations?scriptVersionId=127921968&cellId=13\n\nKAGGLE COMPETITIONS\n\nKaggle Competition: CAFA 5 Protein Function Prediction\nhttps://www.kaggle.com/competitions/cafa-5-protein-function-prediction/discussion?sort=published&page=3\n\nKaggle Competition: Novozymes Enzyme Stability Prediction\nhttps://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction\n\nKaggle Competition: Open Problems - Multimodal Single-Cell Integration\nhttps://www.kaggle.com/competitions/open-problems-multimodal\n\n#AlphaFold on Kaggle\n\nDisplay Test Protein Using AlphaFold v2.1.0 By Chris Deotte\nhttps://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/354982\n\nAlphaFold, ColabFold, ESMFold, OmegaFold? ... or DALL-E-fold? By HengCK23\nhttps://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/356799\n\nIs any part of ESMFold better than AlphaFold? By Tilll (tilli7)\nhttps://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/364127\n\nESMFold API available - By Dieter\nhttps://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/363651\n\nAlphaFold and mutation - By CPMP\nhttps://www.kaggle.com/competitions/novozymes-enzyme-stability-prediction/discussion/364592\n\nAlphaFold Protein Structure Database: https://alphafold.ebi.ac.uk/\n\n#Good Luck on your Predictions: Alea iacta est!", "2433472": "Wow that is so great!", "2435729": "it is a good article. amazing👏", "2432259": "That was a good article to read. I've worked with proteins as a Bioinformatician before joining kaggle.. infact that was one of my major motivations to join the forum. Before reading it, I didn't know kaggle has hosted this much protein related competitions..", "2428545": "Thanks for sharing! Just a little curious, How do you get so fast in every competition? Every time there is a new competition, I always immediately see a brief survey from you or some familiar faces. You guys probably do not have expertise in every single field there is. How do you manage to keep track of all these related works?", "2428595": "", "2441943": "Amazing article, thanks for sharing!", "2438228": "useful,thanks\n" } }