{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2011:WKMMXCI7UY3E3EK6XRB35B2KMR","short_pith_number":"pith:WKMMXCI7","schema_version":"1.0","canonical_sha256":"b298cb891fa6364d915ebc43be874a64535e5c266630dca34246502cf1b6d5c1","source":{"kind":"arxiv","id":"1110.6469","version":1},"attestation_state":"computed","paper":{"title":"An Algorithm for the Stochastic Simulation of Gene Expression and Heterogeneous Population Dynamics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.bio-ph","q-bio.QM"],"primary_cat":"physics.comp-ph","authors_text":"Daniel A. Charlebois, Dawn Fraser, Jukka Intosalmi, Mads Kaern","submitted_at":"2011-10-28T21:26:16Z","abstract_excerpt":"We present an algorithm for the stochastic simulation of gene expression and heterogeneous population dynamics. The algorithm combines an exact method to simulate molecular-level fluctuations in single cells and a constant-number Monte Carlo method to simulate time-dependent statistical characteristics of growing cell populations. To benchmark performance, we compare simulation results with steadystate and time-dependent analytical solutions for several scenarios, including steadystate and time-dependent gene expression, and the effects on population heterogeneity of cell growth, division, and"},"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":"1110.6469","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.comp-ph","submitted_at":"2011-10-28T21:26:16Z","cross_cats_sorted":["physics.bio-ph","q-bio.QM"],"title_canon_sha256":"9009111efd4c0e8460ae7abed4833b750672357e7d11b87b566d05481096b0a2","abstract_canon_sha256":"fa6f6e21a13a05fcc99ce0268a52b38f5c3b4c7c271e62160959d32d244a75b3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:08:13.575991Z","signature_b64":"fuZAr6uPdQroh02Ig3BCIaf8uogY3/PodgagKqZMA4yc/bpLlJq1t84ag6nWCHavaSWKerw06ATC/HTkYyPuCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b298cb891fa6364d915ebc43be874a64535e5c266630dca34246502cf1b6d5c1","last_reissued_at":"2026-05-18T01:08:13.575431Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:08:13.575431Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"An Algorithm for the Stochastic Simulation of Gene Expression and Heterogeneous Population Dynamics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.bio-ph","q-bio.QM"],"primary_cat":"physics.comp-ph","authors_text":"Daniel A. Charlebois, Dawn Fraser, Jukka Intosalmi, Mads Kaern","submitted_at":"2011-10-28T21:26:16Z","abstract_excerpt":"We present an algorithm for the stochastic simulation of gene expression and heterogeneous population dynamics. The algorithm combines an exact method to simulate molecular-level fluctuations in single cells and a constant-number Monte Carlo method to simulate time-dependent statistical characteristics of growing cell populations. To benchmark performance, we compare simulation results with steadystate and time-dependent analytical solutions for several scenarios, including steadystate and time-dependent gene expression, and the effects on population heterogeneity of cell growth, division, and"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1110.6469","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":""},"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":"1110.6469","created_at":"2026-05-18T01:08:13.575549+00:00"},{"alias_kind":"arxiv_version","alias_value":"1110.6469v1","created_at":"2026-05-18T01:08:13.575549+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1110.6469","created_at":"2026-05-18T01:08:13.575549+00:00"},{"alias_kind":"pith_short_12","alias_value":"WKMMXCI7UY3E","created_at":"2026-05-18T12:26:44.992195+00:00"},{"alias_kind":"pith_short_16","alias_value":"WKMMXCI7UY3E3EK6","created_at":"2026-05-18T12:26:44.992195+00:00"},{"alias_kind":"pith_short_8","alias_value":"WKMMXCI7","created_at":"2026-05-18T12:26:44.992195+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/WKMMXCI7UY3E3EK6XRB35B2KMR","json":"https://pith.science/pith/WKMMXCI7UY3E3EK6XRB35B2KMR.json","graph_json":"https://pith.science/api/pith-number/WKMMXCI7UY3E3EK6XRB35B2KMR/graph.json","events_json":"https://pith.science/api/pith-number/WKMMXCI7UY3E3EK6XRB35B2KMR/events.json","paper":"https://pith.science/paper/WKMMXCI7"},"agent_actions":{"view_html":"https://pith.science/pith/WKMMXCI7UY3E3EK6XRB35B2KMR","download_json":"https://pith.science/pith/WKMMXCI7UY3E3EK6XRB35B2KMR.json","view_paper":"https://pith.science/paper/WKMMXCI7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1110.6469&json=true","fetch_graph":"https://pith.science/api/pith-number/WKMMXCI7UY3E3EK6XRB35B2KMR/graph.json","fetch_events":"https://pith.science/api/pith-number/WKMMXCI7UY3E3EK6XRB35B2KMR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WKMMXCI7UY3E3EK6XRB35B2KMR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WKMMXCI7UY3E3EK6XRB35B2KMR/action/storage_attestation","attest_author":"https://pith.science/pith/WKMMXCI7UY3E3EK6XRB35B2KMR/action/author_attestation","sign_citation":"https://pith.science/pith/WKMMXCI7UY3E3EK6XRB35B2KMR/action/citation_signature","submit_replication":"https://pith.science/pith/WKMMXCI7UY3E3EK6XRB35B2KMR/action/replication_record"}},"created_at":"2026-05-18T01:08:13.575549+00:00","updated_at":"2026-05-18T01:08:13.575549+00:00"}