Abstract
Psoriasis is an immune-mediated inflammatory and hyperproliferative skin condition affecting ∼2% of the US population, with a total annual cost of around 3 billion dollars. Despite the successes of drug development, there can be significant variation in treatment response, which can correlate with patients’ genetic variations and baseline skin genomic profiles. However, no study has integrated multiomic information to enhance drug response assessment, potentially because this data is rarely available from the same cohort, and current modeling techniques are limited in their ability to robustly integrate partially overlapping multi-view data.
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