Supplementary File 4 from Bayesian Machine Learning Enables Identification of Transcriptional Network Disruptions Associated with Drug-Resistant Prostate Cancer

Supplementary File 4 from Bayesian Machine Learning Enables Identification of Transcriptional Network Disruptions Associated with Drug-Resistant Prostate Cancer

<p>Excel file with regulon edges and ChIP-seq enrichment scores for TraRe, GRNboost2 and ARACNE-AP</p>

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Tác giả chính:	Charles Blatti (15292859) (author)
Tác giả khác:	Jesús de la Fuente (15292862) (author), Huanyao Gao (14962434) (author), Irene Marín-Goñi (15292865) (author), Zikun Chen (15292868) (author), Sihai D. Zhao (15292871) (author), Winston Tan (15035292) (author), Richard Weinshilboum (15292874) (author), Krishna R. Kalari (15099627) (author), Liewei Wang (14962464) (author), Mikel Hernaez (15292877) (author)
Được phát hành:	2025
Những chủ đề:	Cancer Molecular and Cellular Biology Therapeutic Research and Development Methods and Technology Computational Methods Artificial intelligence & machine learning Drug Resistance Novel mechanisms Regulation of gene expression in drug resistance Gene Regulation Genitourinary Cancers Prostate cancer Systems Biology
Các nhãn:	Thêm thẻ Không có thẻ, Là người đầu tiên thẻ bản ghi này!

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Data file S5 from Targeting STAT5 Signaling Overcomes Resistance to IDH Inhibitors in Acute Myeloid Leukemia through Suppression of Stemness
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