De novo protein design by deep network hallucination
bioRxiv 10.1101/2020.07.22.211482, v1 (23 July 2020). The bioRxiv details API gives version 1 dated 2020-07-23 and links the published version 10.1038/s41586-021-04184-w.
- Issued by
- No issuing record yet. A missing record is a gap in coverage.
- Authors credited
- No authorship claim recorded yet. The source record lists Anishchenko I, Chidyausiku TM, Ovchinnikov S, Pellock SJ and Baker D.
- Dates
- No date claim recorded yet. The source record gives the publication date as 2020-07-23.
- Exact source
- De novo protein design by deep network hallucination (bioRxiv v1) bioRxiv (details API) · published 2020-07-23 · Retrieved for the candidate pack on 2026-10-30 (SHA-256 275259bdb35bb6a61c57c69729653085d6fb43943f49a28e111f28d31260e7cd). bioRxiv details API record (JSON) for v1 of 2020-07-23, with the v1 abstract; the bioRxiv HTML page was not fetched (rate-limited route).
Appears in
- AI in science →1 record on this document
Versions
No other versions of this document are recorded. The evidence applies to the source version listed above. Other versions, such as a preprint, working paper or journal publication, are not identified or substituted.
Documentary relations
Each relation is listed separately. Citing, crediting and reporting the use of a method are different acts, and none of them shows agreement or influence by itself.
Articulates · 1
Propositions whose criterion a passage of this document meets. The record says what the text states, in its register; it is not evidence that the proposition is true.
- Machine-learning methods make proteins with new functions designableThe bioRxiv preprint "De novo protein design by deep network hallucination" (Anishchenko, Chidyausiku, Ovchinnikov, Pellock and Baker, v1 of 23 July 2020) states that deep networks trained to predict native protein structures can be inverted to design new proteins and should contribute to the de novo design of proteins with new functions.2020-07-23 · publication · Stated in source · Supported Inspect claim & evidence ↗Machine-learning methods make proteins with new functions designable: propositions page →
Not recorded for this document: cites · cited by · explicitly credits · reports using a method from · method reported as used by · applies parts of · parts applied by · discusses · reports evaluation of. A missing record does not show that the relation does not exist.