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Article

MOMA: a multi-task attention learning algorithm for multi-omics data interpretation and classification.

Bioinformatics (Oxford, England) - 12 Apr 2022

Moon Sehwan, Lee Hyunju

Abstract excerpt

MOTIVATION: Accurate diagnostic classification and biological interpretation are important in biology and medicine, which are data-rich sciences. Thus, integration of different data types is necessary for the high predictive accuracy of clinical phenotypes, and more comprehensive analyses for predicting the prognosis of complex diseases are required. RESULTS: Here, we propose a novel multi-task attention learning...

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Identifiers

PMID: 35157023
DOI: 10.1093/bioinformatics/btac080
PMCID: PMC10060719

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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