Back to search

Article

MTM: a multi-task learning framework to predict individualized tissue gene expression profiles

2022-10-21

Abstract excerpt

Predicting tissue expression profiles from peripheral ‘surrogate’ samples, especially blood transcriptome, has become an effective alternative when invasive procedures are not ideal. However, existing approaches ignore tissue-shared intrinsic relevance, inevitably limiting predictive performance. Here, we propose a unified deep learning-based multi-task learning framework, Multi-tissue Transcriptome Mapping (MTM),...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
99f5532b-2e88-5cf2-bf32-81231a933421
DOI
10.1101/2022.10.19.512838
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
MTM: a multi-task learning framework to predict individualized tissue gene expression profilesDOI 10.1101/2022.10.19.512838
Select a neighboring publication to make it the new centre.