{"slug": "mircid-inferred-hub-mirnas-drive-cross-task-improvements-in-drug-mechanistic", "title": "MIRCID: Inferred Hub-miRNAs Drive Cross-Task Improvements in Drug Mechanistic Modeling", "summary": "MIRCID, a framework comparing gene expression with inferred transcription factor activity and miRNA expression, infers 414 pan-cancer hub miRNAs from 977 L1000 landmark genes with a Pearson correlation coefficient of 87.72%, according to the arXiv paper. The framework's 1,298-output variant outperformed SiCmiR on the full-miRNA task, 71.21% versus 67.30%, and miRNA augmentation produced more consistent gains than TF activity in the evaluated comparisons. The authors report that inferred HubmiRs offer a biologically informed recoding of transcriptomic data for perturbational drug modeling, while recovery of measured perturbational miRNA responses requires further validation.", "body_md": "arXiv:2609.21280v1 Announce Type: new \nAbstract: Drug mechanism-of-action (MoA) modeling commonly relies on perturbational transcriptomes, but matched microRNA (miRNA) measurements are often unavailable. Inferred regulatory features offer a scalable way to reuse these data. Here, we present MIRCID, a framework comparing gene expression with inferred transcription factor (TF) activity and miRNA expression across pathway classification and similarity-based MoA retrieval. HubmiRNet infers 414 pan-cancer hub miRNAs (HubmiRs) from 977 L1000 landmark genes, achieving a Pearson correlation coefficient of 87.72\\%; its 1,298-output variant also outperformed SiCmiR on the full-miRNA task (71.21\\% versus 67.30\\%). In the evaluated comparisons, miRNA augmentation provided more consistent gains than TF activity. Generic embedding controls showed model-dependent utility, while complementarity analyses identified a distinct, partially linearly recoverable representation that retained gene-derived structure. Illustrative rescue cases linked improved classification to biologically plausible miRNA patterns in samples with weak transcriptional signatures. These findings support inferred HubmiRs as a biologically informed recoding of transcriptomic data for perturbational drug modeling, while leaving recovery of measured perturbational miRNA responses to further validation.", "url": "https://wpnews.pro/news/mircid-inferred-hub-mirnas-drive-cross-task-improvements-in-drug-mechanistic", "canonical_source": "https://www.machinebrief.com/news/mircid-inferred-hub-mirnas-drive-cross-task-improvements-in-wttl", "published_at": "2026-09-21 04:00:00+00:00", "updated_at": "2026-09-21 04:25:05.952971+00:00", "lang": "en", "topics": ["machine-learning", "ai-research", "artificial-intelligence"], "entities": ["MIRCID", "HubmiRNet", "SiCmiR", "L1000", "arXiv"], "alternates": {"html": "https://wpnews.pro/news/mircid-inferred-hub-mirnas-drive-cross-task-improvements-in-drug-mechanistic", "markdown": "https://wpnews.pro/news/mircid-inferred-hub-mirnas-drive-cross-task-improvements-in-drug-mechanistic.md", "text": "https://wpnews.pro/news/mircid-inferred-hub-mirnas-drive-cross-task-improvements-in-drug-mechanistic.txt", "jsonld": "https://wpnews.pro/news/mircid-inferred-hub-mirnas-drive-cross-task-improvements-in-drug-mechanistic.jsonld"}}