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AlphaFind.metadata.json
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{
"@context": "https://w3id.org/codemeta/3.0",
"@type": "SoftwareSourceCode",
"url": "https://alphafind.fi.muni.cz/",
"applicationCategory": "Biology",
"author": [
{
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"affiliation": {
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"name": "Institute of Computer Science, Masaryk University, Brno, 602 00, Czech Republic"
},
"email": "[email protected]",
"familyName": "Slanináková",
"givenName": "Terézia"
},
{
"@id": "http://orcid.org/0009-0000-2765-8329",
"@type": "Person",
"affiliation": {
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"name": "Faculty of Informatics, Masaryk University, Brno, 602 00, Czech Republic"
},
"email": "[email protected]",
"familyName": "Procházka",
"givenName": "David"
},
{
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"@type": "Person",
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"name": "Institute of Computer Science, Masaryk University, Brno, 602 00, Czech Republic"
},
"email": "[email protected]",
"familyName": "Čillík",
"givenName": "Jakub"
}
],
"maintainer": [
{
"@type": "Person",
"givenName": "Terézia",
"familyName": "Slanináková",
"email": "[email protected]",
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},
{
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"email": "[email protected]",
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}
],
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},
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"roleName": "Developer"
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},
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"roleName": "Maintainer"
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],
"codeRepository": "https://github.com/Coda-Research-Group/AlphaFind.git",
"dateCreated": "2024-02-18",
"dateModified": "2024-02-18",
"datePublished": "2024-02-18",
"description": "AlphaFind is a web-based search engine that allows for structure-based search of the entire AlphaFold Protein Structure Database. Uniprot ID, PDB ID, or Gene Symbol is accepted as input – the engine will return the most similar proteins found within AlphaFold DB, with an option for additional search to extend and refine the results. The search results are grouped by their source organism and displayed along with several similarity metrics. 3D visualizations of the structural superposition of the proteins are provided, and text filters can be used to find specific organisms or Uniprot IDs. For details about the methodology and usage, please see the manual. This website is free and open to all users and there is no login requirement.",
"downloadUrl": "https://github.com/Coda-Research-Group/AlphaFind/archive/refs/heads/main.zip",
"installUrl": "https://github.com/Coda-Research-Group/AlphaFind#Installation",
"funder": {
"type": "Organization",
"name": "Czech Science Foundation"
},
"identifier": "https://zenodo.org/doi/10.5281/zenodo.11085862",
"keywords": [
"similarity search",
"structural similarity",
"proteins",
"AlphaFold",
"AFDB"
],
"license": "https://spdx.org/licenses/MIT",
"name": "AlphaFind",
"operatingSystem": [
"Linux",
"Windows",
"MacOS"
],
"programmingLanguage": [
"Python",
"TypeScript",
"JavaScript",
"Shell",
"HTML",
"SCSS"
],
"releaseNotes": "Initial Release",
"softwareRequirements": "Docker",
"version": "1.0.0",
"developmentStatus": "active",
"funding": "GF23-07040K",
"isSourceCodeOf": "https://alphafind.fi.muni.cz/",
"issueTracker": "https://github.com/Coda-Research-Group/AlphaFind/issues",
"contIntegration": "https://github.com/Coda-Research-Group/AlphaFind/actions",
"citation": [
{
"@type": "ScholarlyArticle",
"name": "AlphaFind: discover structure similarity across the proteome in AlphaFold DB",
"author": [
"Procházka, D.",
"Slanináková, T.",
"Olha, J.",
"Rošinec, A.",
"Grešová, K.",
"Jánošová, M.",
"Čillík, J.",
"Porubská J.",
"Svobodová R.",
"Dohnal V.",
"Antol, M."
],
"url": "https://doi.org/10.1093/nar/gkae397",
"datePublished": "2024"
}
],
"referencePublication": [
{
"@type": "ScholarlyArticle",
"name": "AlphaFind: discover structure similarity across the proteome in AlphaFold DB",
"author": [
"Procházka, D.",
"Slanináková, T.",
"Olha, J.",
"Rošinec, A.",
"Grešová, K.",
"Jánošová, M.",
"Čillík, J.",
"Porubská J.",
"Svobodová R.",
"Dohnal V.",
"Antol, M."
],
"url": "https://doi.org/10.1093/nar/gkae397",
"datePublished": "2024"
}
],
"isPartOf": [
{
"@type": "Dataset",
"name": "AlphaFind: Discover structure similarity across the entire known proteome – data and model",
"url": "https://doi.org/10.48700/datst.d35zf-1ja47",
"description": "AlphaFind is a web-based search engine for fast structure-based searching of the entire AlphaFold DB protein structures. This repository contains compact vector embeddings for 214M protein structures, grouped into 2000 clusters, along with a classification neural network, enabling efficient pre-filtering of candidate answers for protein similarity searches.",
"license": "https://creativecommons.org/licenses/by/4.0/"
},
{
"@type": "Dataset",
"name": "AlphaFold Database",
"description": "The AlphaFold Database (AFDB) is a collection of over 214 million protein structure models, each with a unique identifier. These models are derived from the AlphaFold protein structure prediction algorithm and are used for a variety of scientific and research purposes.",
"url": "https://github.com/google-deepmind/alphafold/tree/main/afdb",
"license": "https://www.apache.org/licenses/LICENSE-2.0"
}
]
}