{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:7PHXLMDAI37QMIPHKC3MTIDVHS","short_pith_number":"pith:7PHXLMDA","schema_version":"1.0","canonical_sha256":"fbcf75b06046ff0621e750b6c9a0753cb0a3c1b8dccf37985933fc68175e667f","source":{"kind":"arxiv","id":"2007.13737","version":1},"attestation_state":"computed","paper":{"title":"BIDEAL: A Toolbox for Bicluster Analysis -- Generation, Visualization and Validation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.HC","q-bio.QM"],"primary_cat":"cs.OH","authors_text":"Nishchal K. Verma, P. Agrawal, S. Dixit, S. Sengupta, T. Sharma, V. Singh","submitted_at":"2020-07-26T15:24:53Z","abstract_excerpt":"This paper introduces a novel toolbox named BIDEAL for the generation of biclusters, their analysis, visualization, and validation. The objective is to facilitate researchers to use forefront biclustering algorithms embedded on a single platform. A single toolbox comprising various biclustering algorithms play a vital role to extract meaningful patterns from the data for detecting diseases, biomarkers, gene-drug association, etc. BIDEAL consists of seventeen biclustering algorithms, three biclusters visualization techniques, and six validation indices. The toolbox can analyze several types of "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2007.13737","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.OH","submitted_at":"2020-07-26T15:24:53Z","cross_cats_sorted":["cs.HC","q-bio.QM"],"title_canon_sha256":"9f5b2beaa7430244a34dbcf8683384c97951d9064cb2ad2c55e27182a18e7182","abstract_canon_sha256":"1a0d7dc61468eee59227a4344fcc5269741d9b23ccf1c44d5b7d7855202205b8"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:22:52.302198Z","signature_b64":"+VET3eWchJba1rgi5MQM9/3yG+m7Gk9Tu94dDvpS8bWDW8FAbBp3dXMJw9rb5DvGNAwTVUu22EEVPpQN1/LyCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fbcf75b06046ff0621e750b6c9a0753cb0a3c1b8dccf37985933fc68175e667f","last_reissued_at":"2026-07-05T01:22:52.301820Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:22:52.301820Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"BIDEAL: A Toolbox for Bicluster Analysis -- Generation, Visualization and Validation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.HC","q-bio.QM"],"primary_cat":"cs.OH","authors_text":"Nishchal K. Verma, P. Agrawal, S. Dixit, S. Sengupta, T. Sharma, V. Singh","submitted_at":"2020-07-26T15:24:53Z","abstract_excerpt":"This paper introduces a novel toolbox named BIDEAL for the generation of biclusters, their analysis, visualization, and validation. The objective is to facilitate researchers to use forefront biclustering algorithms embedded on a single platform. A single toolbox comprising various biclustering algorithms play a vital role to extract meaningful patterns from the data for detecting diseases, biomarkers, gene-drug association, etc. BIDEAL consists of seventeen biclustering algorithms, three biclusters visualization techniques, and six validation indices. The toolbox can analyze several types of "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2007.13737","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/2007.13737/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2007.13737","created_at":"2026-07-05T01:22:52.301881+00:00"},{"alias_kind":"arxiv_version","alias_value":"2007.13737v1","created_at":"2026-07-05T01:22:52.301881+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2007.13737","created_at":"2026-07-05T01:22:52.301881+00:00"},{"alias_kind":"pith_short_12","alias_value":"7PHXLMDAI37Q","created_at":"2026-07-05T01:22:52.301881+00:00"},{"alias_kind":"pith_short_16","alias_value":"7PHXLMDAI37QMIPH","created_at":"2026-07-05T01:22:52.301881+00:00"},{"alias_kind":"pith_short_8","alias_value":"7PHXLMDA","created_at":"2026-07-05T01:22:52.301881+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/7PHXLMDAI37QMIPHKC3MTIDVHS","json":"https://pith.science/pith/7PHXLMDAI37QMIPHKC3MTIDVHS.json","graph_json":"https://pith.science/api/pith-number/7PHXLMDAI37QMIPHKC3MTIDVHS/graph.json","events_json":"https://pith.science/api/pith-number/7PHXLMDAI37QMIPHKC3MTIDVHS/events.json","paper":"https://pith.science/paper/7PHXLMDA"},"agent_actions":{"view_html":"https://pith.science/pith/7PHXLMDAI37QMIPHKC3MTIDVHS","download_json":"https://pith.science/pith/7PHXLMDAI37QMIPHKC3MTIDVHS.json","view_paper":"https://pith.science/paper/7PHXLMDA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2007.13737&json=true","fetch_graph":"https://pith.science/api/pith-number/7PHXLMDAI37QMIPHKC3MTIDVHS/graph.json","fetch_events":"https://pith.science/api/pith-number/7PHXLMDAI37QMIPHKC3MTIDVHS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/7PHXLMDAI37QMIPHKC3MTIDVHS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/7PHXLMDAI37QMIPHKC3MTIDVHS/action/storage_attestation","attest_author":"https://pith.science/pith/7PHXLMDAI37QMIPHKC3MTIDVHS/action/author_attestation","sign_citation":"https://pith.science/pith/7PHXLMDAI37QMIPHKC3MTIDVHS/action/citation_signature","submit_replication":"https://pith.science/pith/7PHXLMDAI37QMIPHKC3MTIDVHS/action/replication_record"}},"created_at":"2026-07-05T01:22:52.301881+00:00","updated_at":"2026-07-05T01:22:52.301881+00:00"}