{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:VJROLVSKDW2NDI5GWWV4MUFGDT","short_pith_number":"pith:VJROLVSK","canonical_record":{"source":{"id":"2005.10831","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2020-05-21T16:02:29Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"423b92ef02a3f3a18191f2eaf731f12dca725e53b47cce38dacb7d6817d83812","abstract_canon_sha256":"cc454df05870225cf251f19ffbe679e7ac0b37b8d80881cf885716f4b0415c07"},"schema_version":"1.0"},"canonical_sha256":"aa62e5d64a1db4d1a3a6b5abc650a61ce664926b2d5a261df1721386dbc94e60","source":{"kind":"arxiv","id":"2005.10831","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2005.10831","created_at":"2026-07-05T01:05:03Z"},{"alias_kind":"arxiv_version","alias_value":"2005.10831v1","created_at":"2026-07-05T01:05:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2005.10831","created_at":"2026-07-05T01:05:03Z"},{"alias_kind":"pith_short_12","alias_value":"VJROLVSKDW2N","created_at":"2026-07-05T01:05:03Z"},{"alias_kind":"pith_short_16","alias_value":"VJROLVSKDW2NDI5G","created_at":"2026-07-05T01:05:03Z"},{"alias_kind":"pith_short_8","alias_value":"VJROLVSK","created_at":"2026-07-05T01:05:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:VJROLVSKDW2NDI5GWWV4MUFGDT","target":"record","payload":{"canonical_record":{"source":{"id":"2005.10831","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2020-05-21T16:02:29Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"423b92ef02a3f3a18191f2eaf731f12dca725e53b47cce38dacb7d6817d83812","abstract_canon_sha256":"cc454df05870225cf251f19ffbe679e7ac0b37b8d80881cf885716f4b0415c07"},"schema_version":"1.0"},"canonical_sha256":"aa62e5d64a1db4d1a3a6b5abc650a61ce664926b2d5a261df1721386dbc94e60","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:05:03.085795Z","signature_b64":"rsj8jUBi9WUIQdslR9wervD2MoSfLYcY41BQw+yBMJNsCxohkOu5hE9fMJl1LqTzxRdOpXHN9iztX9Vx950vAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aa62e5d64a1db4d1a3a6b5abc650a61ce664926b2d5a261df1721386dbc94e60","last_reissued_at":"2026-07-05T01:05:03.085298Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:05:03.085298Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2005.10831","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:05:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BCk+1kprVKxP/H91H8t9G4Vzk3eSd2z2HZLzfYY5UF+E/WbK+Pi/+JlyV+MJJQkLNvKlhyR12P08ZaefypBHDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T08:10:50.794027Z"},"content_sha256":"0dc48d486b37d9d369640551828e11ccb0f4426f893916715783ea708ba481bb","schema_version":"1.0","event_id":"sha256:0dc48d486b37d9d369640551828e11ccb0f4426f893916715783ea708ba481bb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:VJROLVSKDW2NDI5GWWV4MUFGDT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Repurpose Open Data to Discover Therapeutics for COVID-19 using Deep Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"q-bio.QM","authors_text":"Feixiong Cheng, George Karypis, Tengfei Ma, Xiang Song, Xiangxiang Zeng, Xiaoqin Pan, Yadi Zhou, Yuan Hou, Zheng Zhang","submitted_at":"2020-05-21T16:02:29Z","abstract_excerpt":"There have been more than 850,000 confirmed cases and over 48,000 deaths from the human coronavirus disease 2019 (COVID-19) pandemic, caused by novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), in the United States alone. However, there are currently no proven effective medications against COVID-19. Drug repurposing offers a promising way for the development of prevention and treatment strategies for COVID-19. This study reports an integrative, network-based deep learning methodology to identify repurposable drugs for COVID-19 (termed CoV-KGE). Specifically, we built a comprehe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2005.10831","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2005.10831/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:05:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"N4cghvZaUZURm2Zyf5UW1qNcA7u6f1n77yTW/OGjzusP5KYTmMhj6xM3OcsHGcY2PJXXcHIvn30cZ93VUw0TBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T08:10:50.794613Z"},"content_sha256":"76158327fe90b2dd2f716fe6bde6f068623b8c8dcfa6a002a386c768d838f321","schema_version":"1.0","event_id":"sha256:76158327fe90b2dd2f716fe6bde6f068623b8c8dcfa6a002a386c768d838f321"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VJROLVSKDW2NDI5GWWV4MUFGDT/bundle.json","state_url":"https://pith.science/pith/VJROLVSKDW2NDI5GWWV4MUFGDT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VJROLVSKDW2NDI5GWWV4MUFGDT/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-01T08:10:50Z","links":{"resolver":"https://pith.science/pith/VJROLVSKDW2NDI5GWWV4MUFGDT","bundle":"https://pith.science/pith/VJROLVSKDW2NDI5GWWV4MUFGDT/bundle.json","state":"https://pith.science/pith/VJROLVSKDW2NDI5GWWV4MUFGDT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VJROLVSKDW2NDI5GWWV4MUFGDT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:VJROLVSKDW2NDI5GWWV4MUFGDT","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"cc454df05870225cf251f19ffbe679e7ac0b37b8d80881cf885716f4b0415c07","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2020-05-21T16:02:29Z","title_canon_sha256":"423b92ef02a3f3a18191f2eaf731f12dca725e53b47cce38dacb7d6817d83812"},"schema_version":"1.0","source":{"id":"2005.10831","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2005.10831","created_at":"2026-07-05T01:05:03Z"},{"alias_kind":"arxiv_version","alias_value":"2005.10831v1","created_at":"2026-07-05T01:05:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2005.10831","created_at":"2026-07-05T01:05:03Z"},{"alias_kind":"pith_short_12","alias_value":"VJROLVSKDW2N","created_at":"2026-07-05T01:05:03Z"},{"alias_kind":"pith_short_16","alias_value":"VJROLVSKDW2NDI5G","created_at":"2026-07-05T01:05:03Z"},{"alias_kind":"pith_short_8","alias_value":"VJROLVSK","created_at":"2026-07-05T01:05:03Z"}],"graph_snapshots":[{"event_id":"sha256:76158327fe90b2dd2f716fe6bde6f068623b8c8dcfa6a002a386c768d838f321","target":"graph","created_at":"2026-07-05T01:05:03Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2005.10831/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"There have been more than 850,000 confirmed cases and over 48,000 deaths from the human coronavirus disease 2019 (COVID-19) pandemic, caused by novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), in the United States alone. However, there are currently no proven effective medications against COVID-19. Drug repurposing offers a promising way for the development of prevention and treatment strategies for COVID-19. This study reports an integrative, network-based deep learning methodology to identify repurposable drugs for COVID-19 (termed CoV-KGE). Specifically, we built a comprehe","authors_text":"Feixiong Cheng, George Karypis, Tengfei Ma, Xiang Song, Xiangxiang Zeng, Xiaoqin Pan, Yadi Zhou, Yuan Hou, Zheng Zhang","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2020-05-21T16:02:29Z","title":"Repurpose Open Data to Discover Therapeutics for COVID-19 using Deep Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2005.10831","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:0dc48d486b37d9d369640551828e11ccb0f4426f893916715783ea708ba481bb","target":"record","created_at":"2026-07-05T01:05:03Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"cc454df05870225cf251f19ffbe679e7ac0b37b8d80881cf885716f4b0415c07","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2020-05-21T16:02:29Z","title_canon_sha256":"423b92ef02a3f3a18191f2eaf731f12dca725e53b47cce38dacb7d6817d83812"},"schema_version":"1.0","source":{"id":"2005.10831","kind":"arxiv","version":1}},"canonical_sha256":"aa62e5d64a1db4d1a3a6b5abc650a61ce664926b2d5a261df1721386dbc94e60","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aa62e5d64a1db4d1a3a6b5abc650a61ce664926b2d5a261df1721386dbc94e60","first_computed_at":"2026-07-05T01:05:03.085298Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:05:03.085298Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rsj8jUBi9WUIQdslR9wervD2MoSfLYcY41BQw+yBMJNsCxohkOu5hE9fMJl1LqTzxRdOpXHN9iztX9Vx950vAA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:05:03.085795Z","signed_message":"canonical_sha256_bytes"},"source_id":"2005.10831","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0dc48d486b37d9d369640551828e11ccb0f4426f893916715783ea708ba481bb","sha256:76158327fe90b2dd2f716fe6bde6f068623b8c8dcfa6a002a386c768d838f321"],"state_sha256":"d2949942cae1320b87c1c99f3a37710a81e4277924776f37025cd4356f7fef39"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MU+Y/irbxOosB9jt6VvY15jAUJmte4bkkvWUVvLVZ9wb6Wx0a0Kx+HOxbSTZEWVquSuKh1tEqcSenAvagn9lCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-01T08:10:50.800346Z","bundle_sha256":"7e371853bec64b073c218d861bbd657eec486701bc3dc6e6f7fb6f67d57353f7"}}