{"id":15118912,"url":"https://github.com/rdkit/benchmarking_platform","last_synced_at":"2025-07-24T03:06:49.144Z","repository":{"id":9304978,"uuid":"11143762","full_name":"rdkit/benchmarking_platform","owner":"rdkit","description":null,"archived":false,"fork":false,"pushed_at":"2022-12-19T16:47:27.000Z","size":79678,"stargazers_count":26,"open_issues_count":4,"forks_count":20,"subscribers_count":5,"default_branch":"master","last_synced_at":"2025-04-12T13:52:11.806Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/rdkit.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2013-07-03T06:41:03.000Z","updated_at":"2024-09-11T14:57:16.000Z","dependencies_parsed_at":"2023-01-11T20:11:54.801Z","dependency_job_id":null,"html_url":"https://github.com/rdkit/benchmarking_platform","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/rdkit/benchmarking_platform","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rdkit%2Fbenchmarking_platform","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rdkit%2Fbenchmarking_platform/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rdkit%2Fbenchmarking_platform/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rdkit%2Fbenchmarking_platform/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/rdkit","download_url":"https://codeload.github.com/rdkit/benchmarking_platform/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rdkit%2Fbenchmarking_platform/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":266786798,"owners_count":23983871,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-07-24T02:00:09.469Z","response_time":99,"last_error":null,"robots_txt_status":null,"robots_txt_updated_at":null,"robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-09-26T01:53:40.187Z","updated_at":"2025-07-24T03:06:48.944Z","avatar_url":"https://github.com/rdkit.png","language":"Python","funding_links":[],"categories":["Ranked by starred repositories"],"sub_categories":[],"readme":"Benchmarking Platform\n=====================\noriginal version presented in \nS. Riniker, G. Landrum, J. Cheminf., 5, 26 (2013),\nDOI: 10.1186/1758-2946-5-26,\nURL: http://www.jcheminf.com/content/5/1/26\n\nextended version presented in\nS. Riniker, N. Fechner, G. Landrum, J. Chem. Inf. Model., 53, 2829, (2013),\nDOI: 10.1021/ci400466r,\nURL: http://pubs.acs.org/doi/abs/10.1021/ci400466r\n\nGENERAL USAGE NOTES\n-------------------\nThe virtual-screening process implemented by the benchmarking\nplatform is divided into three steps:\n\n1) Scoring\n\n2) Validation\n\n3) Analysis\n\nThe three steps are run separately and read in the output of the\nprevious step. In the scoring step, the data from the directories\ncompounds and query_lists is read in.\n\nThe directory compounds contains lists of compounds for 118 targets\nfrom three public data sources: MUV, DUD and ChEMBL. The compound\nlists contain the external ID, the internal ID and the SMILES of\neach compound.\n\nThere are three subsets of targets available:\n\nsubset I: \n  88 targets from MUV, DUD \u0026 ChEMBL described in J. Cheminf., 5, 26 (2013)\n  \nsubset I filtered: \n  69 targets from MUV, DUD \u0026 ChEMBL filtered for difficulty\n  described in JCIM (2013), online\n  \nsubset II:\n  37 targets from ChEMBL designed for a second VS use case\n  described in JCIM (2013), online\n\nThe directory query_lists contains training lists for each target\nwith the indices of randomly selected active and inactive molecules.\nTraining lists with 5, 10 or 20 active molecules are available.\nThe number of training decoys is 20 % of the decoys for subsets I\nand 10 % for subset II.\n\nThe scripts are written in Python and use the open-source\ncheminformatics library RDKit (www.rdkit.org) and\nmachine-learning library scikit-learn (www.scikit-learn.org).\n\nRunning a script with the option [--help] gives a description of the \nrequired and optional input parameters of the script.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frdkit%2Fbenchmarking_platform","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frdkit%2Fbenchmarking_platform","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frdkit%2Fbenchmarking_platform/lists"}