[{"_1":2,"_159":-5,"_160":-5},"loaderData",{"_3":4,"_17":18,"_25":26,"_138":139},"root",{"_5":-5,"_6":-7,"_7":8,"_9":-7,"_10":11,"_12":-7,"_13":14,"_15":16},"currentUser","primaryEmail","siteVerification","6LeIxAcTAAAAAJcZVRqyHh71UMIEGNQ_MXjiZKhI","toast","enableDev",false,"incidentStatus","theme","system","contrast","normal","routes/_layout",{"_19":-5,"_20":21,"_22":21,"_23":11,"_24":21},"username","isAskGordonEnabled",true,"isUsingNewTemplate","showMinimalLanding","showHoneypotTrap","routes/_layout.r.$namespace.$reponame",{"_27":28,"_29":-5,"_30":11,"_31":11,"_32":33,"_34":35,"_36":-5,"_37":11,"_38":39,"_88":-5,"_89":90,"_129":-5,"_130":11,"_131":21,"_132":11,"_133":-5,"_134":11,"_135":-5,"_136":137},"canonicalUrl","https://hub.docker.com/r/mircare/microbrewery/tags","mcpServer","canSeeDockerfile","canSeeAutobuilds","namespace","mircare","reponame","microbrewery","cloudBuildSource","isAutobuildsAvailable","repo",{"_40":41,"_42":43,"_45":46,"_47":48,"_49":11,"_50":51,"_52":53,"_54":55,"_57":35,"_32":33,"_58":59,"_60":44,"_61":62,"_63":64,"_65":66,"_67":-5,"_68":62,"_69":70,"_71":11,"_72":33,"_73":74,"_79":11,"_80":81,"_85":33,"_86":87},"categories",[],"content_types",[44],"image","date_registered","2021-02-13T16:41:49.463986Z","description","Deep Transfer Learning for alignment-free prediction of protein structure annotations","is_private","last_updated","2021-02-21T21:28:14.418007Z","last_modified","2024-10-16T13:48:34.145251Z","media_types",[56],"application/vnd.docker.container.image.v1+json","name","pull_count",254,"repository_type","star_count",0,"status",1,"status_description","active","source","collaborator_count","full_description","[![PWC](https://camo.githubusercontent.com/6887feb0136db5156c4f4146e3dd2681d06d9c75/68747470733a2f2f692e6372656174697665636f6d6d6f6e732e6f72672f6c2f62792d6e632d73612f342e302f38387833312e706e67)](https://github.com/mircare/Brewery/#license)\n\n# Microbrewery: Deep Transfer Learning for alignment-free prediction of protein structure annotations\n\nThe docker container is available at https://hub.docker.com/r/mircare/microbrewery ([HOWTO](https://github.com/mircare/microbrewery#use-the-docker-image)). \n\nSee https://github.com/mircare/Brewery for profile-based prediction of protein structure annotations.\n\n## Setup\n```\n$ git clone https://github.com/mircare/Microbrewery/ --depth 1 && rm -rf Microbrewery/.git\n```\n\n### Requirements\n1. Python3 (https://www.python.org/downloads/);\n1. NumPy (https://www.scipy.org/scipylib/download.html);\n\n\n## Run Microbrewery\n```\n$ python3 Microbrewery/Microbrewery.py -i Microbrewery/example/2FLGA.fasta --cpu 4 \n```\n\n### Run Microbrewery on multiple sequences\n```\n# To split a FASTA file containing multiple sequences\n$ python3 Microbrewery/split_fasta.py many_sequences.fasta\n\n# To predict all the fasta files in a given directory, e.g. DIRNAME\n$ python3 Microbrewery/multiple_fasta.py -i DIRNAME/ --cpu 4 --fast\n```\n\n## The help of Microbrewery\n```\n$ python3 Microbrewery/Microbrewery.py --help\nusage: Microbrewery.py [-h] [-input fasta_file] [--noSS] [--noTA] [--noSA]\n [--noCD] [--setup]\n\nThis is the standalone of Microbrewery. Run it on a FASTA file to predict its\nSecondary Structure in 3- and 8-classes (Porter5), Solvent Accessibility in 4\nclasses (PaleAle5), Structural Motifs in 14 classes (Porter+5) and Contact\nDensity in 4 classes (BrownAle5).\n\noptional arguments:\n -h, --help show this help message and exit\n -input fasta_file FASTA file containing the protein to predict\n --noSS Skip Secondary Structure prediction\n --noTA Skip Structural Motifs prediction\n --noSA Skip Solvent Accessibility prediction\n --noCD Skip Contact Density prediction\n --setup Initialize Microbrewery from scratch (e.g., required when\n it is moved).\n\nE.g., python3 Microbrewery.py -i example/2FLGA.fasta\n```\n\n### Use the docker image\n```\n# Set the absolute PATHs to the query sequences\n$ docker run --name microbrewery -v /**PATH_to_fasta_to_predict**:/Microbrewery/query \\\n--cap-add IPC_LOCK mircare/microbrewery sleep infinity &\n\n# Run Microbrewery\n$ docker exec microbrewery python3 Microbrewery.py -i query/2FLGA.fasta\n```\n\n## Performances on the 2019_test set of 618 proteins\n| Method | SS3 | SS8 | TA14 | CD4 |\n| :--- | :---: | :---: | :---: | :---: |\n| Microbrewery | 72.6% | 59.2% | 54.8% | 36.8% |51.7%|\n| SPIDER3-single | 71.4% | 57.6% | 50.9% | 32.5% | N/A |\n\n\n## Citation\nIf you use Microbrewery, please cite our Bioinformatics paper:\n```\n@article{torrisi_brewery_2020,\n\ttitle = {Brewery: Deep Learning and deeper profiles for the prediction of 1D protein structure annotations},\n\tdoi = {10.1093/bioinformatics/btaa204},\n\tjournal = {Bioinformatics},\n\tauthor = {Torrisi, Mirko and Pollastri, Gianluca}\n}\n```\n\n\n## References\nBrewery: Deep Learning and deeper profiles for the prediction of 1D protein structure annotations,
\nBioinformatics, Oxford University Press; Mirko Torrisi and Gianluca Pollastri;
\nGuest link: https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa204/5811232?guestAccessKey=9a73ae2a-2cb6-4fe1-b333-a4f3261f02cf.\n\nProtein Structure Annotations; Essentials of Bioinformatics, Volume I. Springer Nature
\nMirko Torrisi and Gianluca Pollastri; Post-print: https://www.researchgate.net/publication/332048741_Protein_Structure_Annotations.\n\nDeeper Profiles and Cascaded Recurrent and Convolutional Neural Networks for state-of-the-art Protein Secondary Structure Prediction, Scientific Reports, Nature Publishing Group; Mirko Torrisi, Manaz Kaleel and Gianluca Pollastri;
\ndoi: https://doi.org/10.1038/s41598-019-48786-x.\n\nPaleAle 5.0: prediction of protein relative solvent accessibility by deep learning, Amino Acids, Springer
\nManaz Kaleel, Mirko Torrisi, Catherine Mooney and Gianluca Pollastri; Guest Link: https://rdcu.be/bNlXS.\n\n\n## License\nThis work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.\n\nEmail us at gianluca[dot]pollastri[at]ucd[dot]ie if you wish to use it for purposes not permitted by the CC BY-NC-SA 4.0.\n\n $\"Creative$ \n","has_starred","hub_user","immutable_tags_settings",{"_75":11,"_76":77},"enabled","rules",[78],".*","is_automated","permissions",{"_82":21,"_83":11,"_84":11},"read","write","admin","user","storage_size",101805923,"orgData","recentTags",[91],{"_92":44,"_93":94,"_95":96,"_97":98,"_99":100,"_50":118,"_119":94,"_120":33,"_121":56,"_57":122,"_123":124,"_125":109,"_126":118,"_127":66,"_128":21},"content_type","creator",5857526,"full_size",101801313,"id",137474067,"images",[101],{"_102":103,"_104":105,"_106":107,"_108":109,"_110":111,"_112":113,"_114":107,"_115":-5,"_116":96,"_63":66,"_117":-5},"architecture","amd64","digest","sha256:e544aec3c1bd09697074a24fd7d6d9130ecb50ed3917d945ac098d6bddc9d3e9","features","","last_pulled","2026-09-30T08:26:36.647240619Z","last_pushed","2021-02-13T16:54:17Z","os","linux","os_features","os_version","size","variant","2021-02-21T21:28:14.110756Z","last_updater","last_updater_username","media_type","latest","repository",11406719,"tag_last_pulled","tag_last_pushed","tag_status","v2","sbxKitMetadata","isPotentialSpam","isHubSbxKitsEnabled","showSbxLogoOverride","sbxTrademarkText","displaySecurityMetadata","tagAttestations","tagsHaveAttestations",[],"routes/_layout.r.$namespace.$reponame.tags",{"_38":140,"_147":148,"_136":157,"_158":11},{"_40":141,"_42":142,"_45":46,"_47":48,"_49":11,"_50":51,"_52":53,"_54":143,"_57":35,"_32":33,"_58":59,"_60":44,"_61":62,"_63":64,"_65":66,"_67":-5,"_68":62,"_69":70,"_71":11,"_72":33,"_73":144,"_79":11,"_80":146,"_85":33,"_86":87},[],[44],[56],{"_75":11,"_76":145},[78],{"_82":21,"_83":11,"_84":11},"tags",{"_149":64,"_150":-5,"_151":-5,"_152":153},"count","next","previous","results",[154],{"_92":44,"_93":94,"_95":96,"_97":98,"_99":155,"_50":118,"_119":94,"_120":33,"_121":56,"_57":122,"_123":124,"_125":109,"_126":118,"_127":66,"_128":21},[156],{"_102":103,"_104":105,"_106":107,"_108":109,"_110":111,"_112":113,"_114":107,"_115":-5,"_116":96,"_63":66,"_117":-5},[],"canDeleteTags","actionData","errors"]

mircare/microbrewery

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