{"entity":{"id":"domain-adaptation","kind":"term","name":"Domain shift and domain adaptation (cell line to patient)","aka":["domain shift","distribution shift","domain adaptation","cell-line to patient transfer","TUGDA","Velodrome","PRECISE","TRANSACT","train-test mismatch"],"tldr":"Domain shift is the mismatch between the data a model was trained on and the data it meets later (cell lines versus tumours, one sequencing platform versus another); domain adaptation is the family of methods that try to bridge it.","summary":"Domain adaptation addresses training a model on one data distribution and applying it to a related but different one (Wikipedia). Cell-line screens are the training data for drug response but patients are the goal, so methods such as PRECISE and TRANSACT (Mourragui and colleagues) align the two distributions in a shared subspace and TUGDA (Peres da Silva and colleagues) weights tasks by their uncertainty during adaptation. Platform shift between RNA-seq and microarray is the same problem one level down.","asOf":"2026-09-24","wikipedia":"https://en.wikipedia.org/wiki/Domain_adaptation","links":[{"label":"Peres da Silva et al., TUGDA: task uncertainty guided domain adaptation for robust generalization of cancer drug response prediction (Bioinformatics 2021)","url":"https://doi.org/10.1093/bioinformatics/btab299"},{"label":"Mourragui et al., PRECISE (Bioinformatics 2019)","url":"https://doi.org/10.1093/bioinformatics/btz372"},{"label":"Mourragui et al., TRANSACT (PNAS 2021)","url":"https://doi.org/10.1073/pnas.2106682118"},{"label":"Wikipedia","url":"https://en.wikipedia.org/wiki/Domain_adaptation"}],"tags":["cansim-terms"],"related":["cancer-ai-vocabulary"],"cancers":[],"sections":[],"technologies":[],"targets":[],"drugs":[],"companies":[],"institutions":[],"pathways":[],"terms":["batch-effects","ood-detection","cell-lines-as-proxy","external-validation"],"trials":[],"people":[],"bottlenecks":[],"keyPapers":[],"journals":[],"dependsOn":[],"notes":["Listed in the CanSim terms map 1.0.0 (docs/onco/terms.json, generated 2026-09-24), CC BY 4.0, attribution: CanSim project, an open, public-data-first cancer foundation-model programme; CanSim page path /terms/domain-adaptation."],"provenance":{"editedBy":"OnCo CanSim terms wave (Wikipedia summaries, standards and project pages, GDC and FDA pages, Europe PMC)","editedOn":"2026-09-24","note":"CanSim terms map 1.0.0 (docs/onco/terms.json, generated 2026-09-24), CC BY 4.0, attribution: CanSim project, an open, public-data-first cancer foundation-model programme"},"category":"Methods and models"},"route":"/terms/domain-adaptation/","neighbours":{"term":[{"id":"batch-effects","kind":"term","name":"Batch effects and harmonisation","route":"/terms/batch-effects/"},{"id":"cancer-ai-vocabulary","kind":"term","name":"Cancer AI vocabulary (CanSim terms map)","route":"/terms/cancer-ai-vocabulary/"},{"id":"cell-lines-as-proxy","kind":"term","name":"Cell lines as a proxy for patients","route":"/terms/cell-lines-as-proxy/"},{"id":"external-validation","kind":"term","name":"External validation","route":"/terms/external-validation/"},{"id":"ood-detection","kind":"term","name":"Out-of-distribution detection (Mahalanobis guard)","route":"/terms/ood-detection/"},{"id":"quantile-normalisation","kind":"term","name":"Quantile normalisation, rank transforms and z-scores","route":"/terms/quantile-normalisation/"}]}}