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Bunne et al. (arXiv v1, 18 September 2024) propose a vision of "AI-powered Virtual Cells" whose representations are learned from biological data and that facilitate in silico experiments to predict and understand cell behaviour. Copy claim link
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Supporting evidence: primary · 1 source
Date 2024-09-18 · publication Records dated 2024 → Role Articulation Register (kind of text) Nonfiction Scope of the passage A proposal and research agenda, in the future tense. Scope and limits The record documents what this text states, in its register; it is not evidence that the proposition is true and implies no influence on or from any other text. A perspective by 42 authors from academia and industry, stating a vision and its requirements; it reports no model. Only the v1 abstract was read.
The evidence 02 primary source Supports the claim
How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities ↗ arXiv · 2024-09-18
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Source excerpt “Here we propose a vision of AI-powered Virtual Cells, where robust representations of cells and cellular systems under different conditions are directly learned from growing biological data across measurements and scales.” Location in source Abstract
How it was read Retrieved directly from the publisher
Machine-checked · 2026-10-30
Source details and check notes Authors Charlotte Bunne; Yusuf Roohani; Yanay Rosen; Stephen R. Quake Version Retrieved for the candidate pack on 2026-10-30 (SHA-256 bc8ed7243e4d486c63c743ee313c5830d6c6d1484f6b9a19ef4a0d8f041ad54c). arXiv abstract page of v1 (18 September 2024); v2 of 14 October 2024 exists and was not read. The author list is partial: it gives the authors the retrieved expression names and leaves out those it abbreviates. Canonical address Open the canonical source ↗ Accessed 2026-10-30 Language English (en) Attribution Charlotte Bunne, Yusuf Roohani, Yanay Rosen, Stephen R. Quake, “How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities”, 2024-09-18. Reuse No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution. Check notes Candidate pack passage, AI in biology (research/ai-in-biology). The quotation (31 words) matched the text retrieved for the candidate pack on 2026-10-30. Matching ignored differences of whitespace, case, quotation marks, dashes and Unicode compatibility forms, so the source’s typography can differ. The authors' stated proposal. No human editorial review. primary source Supports the claim
How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities ↗ arXiv · 2024-09-18
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Cite the original source Cite the original document, not Selekoa. Check these details against it.
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Source excerpt “We envision a future where AI Virtual Cells help identify new drug targets, predict cellular responses to perturbations, as well as scale hypothesis exploration.” Location in source Abstract
How it was read Retrieved directly from the publisher
Machine-checked · 2026-10-30
Source details and check notes Authors Charlotte Bunne; Yusuf Roohani; Yanay Rosen; Stephen R. Quake Version Retrieved for the candidate pack on 2026-10-30 (SHA-256 bc8ed7243e4d486c63c743ee313c5830d6c6d1484f6b9a19ef4a0d8f041ad54c). arXiv abstract page of v1 (18 September 2024); v2 of 14 October 2024 exists and was not read. The author list is partial: it gives the authors the retrieved expression names and leaves out those it abbreviates. Canonical address Open the canonical source ↗ Accessed 2026-10-30 Language English (en) Attribution Charlotte Bunne, Yusuf Roohani, Yanay Rosen, Stephen R. Quake, “How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities”, 2024-09-18. Reuse No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution. Check notes Candidate pack passage, AI in biology (research/ai-in-biology). The quotation (24 words) matched the text retrieved for the candidate pack on 2026-10-30. Matching ignored differences of whitespace, case, quotation marks, dashes and Unicode compatibility forms, so the source’s typography can differ. The predictive capability the authors foresee. No human editorial review. Status and meaning Editorial status. Not reviewed by an editor . An exploratory record that no editor has accepted. This status does not say whether a person has read any linked passage. Each evidence record above shows how it was checked.
Relation. A passage of the document meets the proposition’s criterion. The record documents what the text states, in its register (fiction and satire are labelled); it is not evidence that the proposition is true and implies no influence on or from another text.
Date. Date of the arXiv v1 submission, the expression read.
Record ID aib-arg-p2-bunne-2024