Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample
Genome Biology 23:12, published 2022-01-07; PMC8740374 full-text XML · Peer-reviewed
Evidence
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Evidence table
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17 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| attributes.artifact_sha256 78dbe540c2558585bc7537e0e6563706fdaa329b2708e5dc82b77074379b4a6e Source metadata | Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample No field-specific location recorded Version: Genome Biology 23:12, published 2022-01-07; PMC8740374 full-text XML | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Artifact url https://www.ebi.ac.uk/europepmc/webservices/rest/PMC8740374/fullTextXML Source metadata | Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample No field-specific location recorded Version: Genome Biology 23:12, published 2022-01-07; PMC8740374 full-text XML | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Doi 10.1186/s13059-021-02592-9 Source metadata | Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample No field-specific location recorded Version: Genome Biology 23:12, published 2022-01-07; PMC8740374 full-text XML | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Licence CC-BY-4.0 Source metadata | Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample No field-specific location recorded Version: Genome Biology 23:12, published 2022-01-07; PMC8740374 full-text XML | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Media type application/xml Source metadata | Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample No field-specific location recorded Version: Genome Biology 23:12, published 2022-01-07; PMC8740374 full-text XML | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Publication status peer_reviewed Source metadata | Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample No field-specific location recorded Version: Genome Biology 23:12, published 2022-01-07; PMC8740374 full-text XML | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Retrieved at 2026-10-10T06:04:11Z Source metadata | Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample No field-specific location recorded Version: Genome Biology 23:12, published 2022-01-07; PMC8740374 full-text XML | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Url https://doi.org/10.1186/s13059-021-02592-9 Source metadata | Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample No field-specific location recorded Version: Genome Biology 23:12, published 2022-01-07; PMC8740374 full-text XML | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Version Genome Biology 23:12, published 2022-01-07; PMC8740374 full-text XML Source metadata | Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample No field-specific location recorded Version: Genome Biology 23:12, published 2022-01-07; PMC8740374 full-text XML | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Description Primary source retrieved and hashed for the NeuSomatic SEQC2 follow-up to the somatic variant detection use-case pass. Source metadata | Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample No field-specific location recorded Version: Genome Biology 23:12, published 2022-01-07; PMC8740374 full-text XML | catalogued No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Sources and history
Release 2026-10-10-cbb3da59bc08 · Record review: source checked
Primary source retrieved and hashed for the NeuSomatic SEQC2 follow-up to the somatic variant detection use-case pass.
Technical metadata and extraction receipts
Stable ID: somatic-neusomatic-20261010-source-sahraeian2022
- areas
- dna-genomes
- contexts
- clinical_research
- url
- https://doi.org/10.1186/s13059-021-02592-9
- artifact url
- https://www.ebi.ac.uk/europepmc/webservices/rest/PMC8740374/fullTextXML
- version
- Genome Biology 23:12, published 2022-01-07; PMC8740374 full-text XML
- retrieved at
- 2026-10-10T06:04:11Z
- artifact sha256
- 78dbe540c2558585bc7537e0e6563706fdaa329b2708e5dc82b77074379b4a6e
- doi
- 10.1186/s13059-021-02592-9
- publication status
- peer_reviewed
- licence
- CC-BY-4.0
- media type
- application/xml