M
Michael Ku Yu
Researcher at University of California, San Diego
Publications - 14
Citations - 1194
Michael Ku Yu is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Genome & Epigenomics. The author has an hindex of 10, co-authored 14 publications receiving 820 citations. Previous affiliations of Michael Ku Yu include Toyota Technological Institute at Chicago.
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Journal ArticleDOI
Using deep learning to model the hierarchical structure and function of a cell.
Jianzhu Ma,Michael Ku Yu,Samson Fong,Keiichiro Ono,Eric Sage,Barry Demchak,Roded Sharan,Trey Ideker +7 more
TL;DR: DCell, a VNN embedded in the hierarchical structure of 2,526 subsystems comprising a eukaryotic cell, provides a foundation for decoding the genetics of disease, drug resistance and synthetic life.
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Epigenetic aging signatures in mice livers are slowed by dwarfism, calorie restriction and rapamycin treatment
Tina Wang,Brian Tsui,Jason F. Kreisberg,Neil Robertson,Andrew M. Gross,Michael Ku Yu,Hannah Carter,Holly M. Brown-Borg,Peter D. Adams,Peter D. Adams,Trey Ideker +10 more
TL;DR: This study shows that lifespan-extending conditions can slow molecular changes associated with an epigenetic clock in mice livers, and finds that mice treated with lifespan-Extending interventions were significantly younger in epigenetic age than their untreated, wild-type age-matched controls.
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Systematic Evaluation of Molecular Networks for Discovery of Disease Genes
Justin K. Huang,Daniel E. Carlin,Michael Ku Yu,Wei Zhang,Jason F. Kreisberg,Pablo Tamayo,Trey Ideker +6 more
TL;DR: This work evaluates 21 human genome-wide interaction networks for their ability to recover 446 disease gene sets identified through literature curation, gene expression profiling, or genome- wide association studies to create a parsimonious composite network with both high efficiency and performance.
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Visible Machine Learning for Biomedicine
TL;DR: This work argues for "visible" approaches that guide model structure with experimental biology in biomedicine, including handling of extreme data heterogeneity and lack of mechanistic insight into predictions.
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A global transcriptional network connecting noncoding mutations to changes in tumor gene expression.
Wei Zhang,Ana Bojorquez-Gomez,Daniel Ortiz Velez,Guorong Xu,Kyle S. Sanchez,John Paul Shen,Kevin Chen,Katherine Licon,Collin Melton,Katrina M. Olson,Michael Ku Yu,Justin K. Huang,Hannah Carter,Emma K. Farley,Michael Snyder,Stephanie I. Fraley,Jason F. Kreisberg,Trey Ideker +17 more
TL;DR: An integrative analysis of tumor whole genomes and matched transcriptomes finds that the effects of noncoding mutations on DAAM1, MTG2 and HYI transcription are recapitulated in multiple cancer cell lines and that increasingDAAM1 expression leads to invasive cell migration.