diff --git a/README.md b/README.md index c2c01f8..5c3c293 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,7 @@ # Protein Language Models -This is an [Observable Framework](https://observablehq.com/framework/) app. To install the required dependencies, run: +Data is found at this [gSheet](https://docs.google.com/spreadsheets/d/1iJ7bPG81_yYITVQn-huoQonKTel7GBQ7AMM9AixQbH8/edit?gid=1996577388#gid=1996577388) + ``` npm install diff --git a/package-lock.json b/package-lock.json index 4f40de1..bcb89bc 100644 --- a/package-lock.json +++ b/package-lock.json @@ -10,6 +10,7 @@ "d3-time-format": "^4.1.0" }, "devDependencies": { + "d3": "^7.9", "rimraf": "^5.0.5" }, "engines": { @@ -1282,6 +1283,48 @@ "integrity": "sha512-TrEMa7JGdVm0UThDJSx7ddw5nVm3UJS9o9CCIZ72B1vSyEZoziDqBYP3XIoi/12lKrJR8rE3jeFHMok2F/Mnsg==", "license": "MIT" }, + "node_modules/d3": { + "version": "7.9.0", + "resolved": "https://registry.npmjs.org/d3/-/d3-7.9.0.tgz", + "integrity": 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">=12" + } + }, "node_modules/data-urls": { "version": "5.0.0", "resolved": "https://registry.npmjs.org/data-urls/-/data-urls-5.0.0.tgz", @@ -1437,6 +1795,16 @@ "url": "https://github.com/sponsors/sindresorhus" } }, + "node_modules/delaunator": { + "version": "5.0.1", + "resolved": "https://registry.npmjs.org/delaunator/-/delaunator-5.0.1.tgz", + "integrity": "sha512-8nvh+XBe96aCESrGOqMp/84b13H9cdKbG5P2ejQCh4d4sK9RL4371qou9drQjMhvnPmhWl5hnmqbEE0fXr9Xnw==", + "dev": true, + "license": "ISC", + "dependencies": { + "robust-predicates": "^3.0.2" + } + }, "node_modules/delayed-stream": { "version": "1.0.0", "resolved": "https://registry.npmjs.org/delayed-stream/-/delayed-stream-1.0.0.tgz", @@ -2588,6 +2956,13 @@ "url": "https://github.com/sponsors/isaacs" } }, + "node_modules/robust-predicates": { + "version": "3.0.2", + "resolved": "https://registry.npmjs.org/robust-predicates/-/robust-predicates-3.0.2.tgz", + "integrity": 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(8P+2E),24/32,3.23(P)/2.0(E),1.296 -Apple,M1 Ultra,64GB,Mar 2022,128GB,20 (16P+4E),48/64,3.23(P)/2.0(E),1.296 -Apple,M2,8GB,Jun 2022,24GB,8 (4P+4E),8/10,3.49(P)/2.4(E),1.398 -Apple,M2 Pro,16GB,Jan 2023,32GB,10/12 (6/8P+4E),16/19,3.48(P)/2.4(E),1.398 -Apple,M2 Max,32GB,Jan 2023,96GB,12 (8P+4E),30/38,3.68(P)/2.4(E),1.398 -Apple,M2 Ultra,64GB,Jun 2023,192GB,24 (16P+8E),60/76,3.68(P)/2.4(E),1.398 -Apple,M3,8GB,Oct 2023,24GB,8 (4P+4E),10,4.05(P)/2.7(E),1.5 -Apple,M3 Pro,18GB,Oct 2023,36GB,12 (6P+6E),18,4.05(P)/2.7(E),1.5 -Apple,M3 Max,36GB,Oct 2023,128GB,16 (12P+4E),40,4.05(P)/2.7(E),1.5 -Tinygrad,Tinybox Green,128GB,Oct 2024,,,,, diff --git a/src/data/hardware.tsv.js b/src/data/hardware.tsv.js new file mode 100644 index 0000000..e0d9faf --- /dev/null +++ b/src/data/hardware.tsv.js @@ -0,0 +1,10 @@ +// // spreadsheet 1iJ7bPG81_yYITVQn-huoQonKTel7GBQ7AMM9AixQbH8 +// // gid = 1996577388 + +const url = `https://docs.google.com/spreadsheets/d/1iJ7bPG81_yYITVQn-huoQonKTel7GBQ7AMM9AixQbH8/export?format=tsv&gid=1996577388`; + +(async () => { + const response = await fetch(url); + const text = await response.text(); + process.stdout.write(text); +})(); diff --git a/src/data/protein_language_models.tsv b/src/data/protein_language_models.tsv deleted file mode 100644 index a6909fc..0000000 --- a/src/data/protein_language_models.tsv +++ /dev/null @@ -1,12 +0,0 @@ -Name Publication Publication_URL Publication_Date Version SourceURL WeightURL TotalWeightsSize Architecture Training Data Size License HuggingFace -AlphaFold2 Highly accurate protein structure prediction with AlphaFold https://www.nature.com/articles/s41586-021-03819-2 Jul 2021 v2.3.1 https://github.com/google-deepmind/alphafold https://storage.googleapis.com/alphafold/ ~3GB Transformer-based ~170_000 structures (PDB) Apache 2.0 -AlphaFold2 Multimer Protein complex prediction with AlphaFold-Multimer https://www.biorxiv.org/content/10.1101/2021.10.04.463034v2 Mar 2022 https://github.com/google-deepmind/alphafold https://storage.googleapis.com/alphafold/ ~3GB -ESM2 Language models of protein sequences at the scale of evolution enable accurate structure prediction https://www.science.org/doi/10.1126/science.ade2574 Jan 2023 ESM-2 https://github.com/facebookresearch/esm https://dl.fbaipublicfiles.com/fair-esm/models/ ~3GB Transformer 250M sequences MIT facebook/esm2 -ESMFold High-accuracy protein structure prediction with language models https://www.biorxiv.org/content/10.1101/2022.07.20.500902v2 Dec 2022 v1 https://github.com/facebookresearch/esm Same as ESM2 ~3GB Transformer + Structure Module Based on ESM2 MIT facebook/esmfold -ProteinMPNN Neural network-based protein sequence design https://www.science.org/doi/10.1126/science.add2187 Jul 2022 v1 https://github.com/dauparas/ProteinMPNN https://files.ipd.uw.edu/pub/training/weights/ ~10MB Message Passing Neural Network PDB structures MIT -OpenFold OpenFold: Retraining AlphaFold2 from scratch https://www.biorxiv.org/content/10.1101/2022.11.20.517210v2 Sep 2022 v1.0 https://github.com/aqlaboratory/openfold Available through repo ~3GB Similar to AlphaFold2 Same as AlphaFold2 Apache 2.0 -RoseTTAFold Accurate prediction of protein structures and interactions using a three-track neural network https://pubmed.ncbi.nlm.nih.gov/34282049/ Jul 2021 v1 https://github.com/RosettaCommons/RoseTTAFold Available through repo ~1GB Three-track architecture PDB + MSA data MIT -LigandMPNN Robust deep learning-based protein sequence design using ProteinMPNN https://www.biorxiv.org/content/10.1101/2023.12.22.573103v1 Dec 2023 v1 https://github.com/dauparas/LigandMPNN https://files.ipd.uw.edu/pub/protein_mpnn/ ~20MB Message Passing Neural Network PDB structures MIT -Amplify Functional Protein Design by Artificial Intelligence https://www.biorxiv.org/content/10.1101/2024.09.23.614603v1 Dec 2023 v1 https://github.com/chandar-lab/AMPLIFY Available through repo ~500MB Transformer PDB + UniProt data MIT chandar-lab/AMPLIFY_120M -SaProt SaProt: Protein Language Modeling with Structure-aware Vocabulary https://www.biorxiv.org/content/10.1101/2023.10.01.560349v1 Oct 2023 v1 https://github.com/westlake-repl/SaProt Available through repo ~1GB Transformer with structure-aware tokenization UniProt + PDB data Apache 2.0 -ProstT5 ProstT5: Bilingual Language Model for Protein Sequence and Structure https://www.biorxiv.org/content/10.1101/2023.07.23.550085v1 Jul 23 V1 https://github.com/mheinzinger/ProstT5 Available through repo 11GB MIT "Rostlab/ProstT5_fp16,Rostlab/ProstT5" diff --git a/src/data/protein_language_models.tsv.js b/src/data/protein_language_models.tsv.js new file mode 100644 index 0000000..e306b88 --- /dev/null +++ b/src/data/protein_language_models.tsv.js @@ -0,0 +1,10 @@ +// // spreadsheet 1iJ7bPG81_yYITVQn-huoQonKTel7GBQ7AMM9AixQbH8 +// // gid = 0 + +const url = `https://docs.google.com/spreadsheets/d/1iJ7bPG81_yYITVQn-huoQonKTel7GBQ7AMM9AixQbH8/export?format=tsv&gid=0`; + +(async () => { + const response = await fetch(url); + const text = await response.text(); + process.stdout.write(text); +})(); diff --git a/src/index.md b/src/index.md index 8667cae..b6c9e67 100644 --- a/src/index.md +++ b/src/index.md @@ -3,6 +3,8 @@ title: Protein Language Models toc: true --- +Data is found at this [gSheet](https://docs.google.com/spreadsheets/d/1iJ7bPG81_yYITVQn-huoQonKTel7GBQ7AMM9AixQbH8/edit?gid=1996577388#gid=1996577388) +