Regulatory Programs

Learning regulatory programs by threshold SVD regression.

We formulate a statistical model for the regulation of global gene expression by multiple regulatory programs and propose a thresholding singular value decomposition (T-SVD) regression method for learning such a model from data. Extensive simulations demonstrate that this method offers improved computational speed and higher sensitivity and specificity over competing approaches. The method is u...

Regulatory regimes and state cost containment programs.

Gene-regulatory interactions in embryonic stem cells represent cell-type specific gene regulatory programs

Pluripotency, the ability of embryonic stem cells to differentiate into specialized cell types, is determined by ESC-specific gene regulators such as transcription factors and chromatin modification factors. It is not well understood how ESCs are poised for differentiation, however, and methods are needed for prognosis of the molecular changes in the differentiation of ESCs into specific organs...

Integrative approaches for mining transcriptional regulatory programs in Arabidopsis.

Challenges in modern biology demand shifting focus from components-genes and proteins-to their interacting whole. Integrating information from multiple genomic datasets is seen as a means to this end, capable of providing robust and accurate ways to unravel these functional associations. Integrative strategies, both novel and adapted from other well-studied organisms, are being employed in the ...

MicroRNAs in control of gene regulatory programs in diabetic vasculopathy.

Diabetes is generally associated with vasculopathy, which contains both microvascular and macrovascular complications, associated with high morbidity and mortality. Currently, despite interventional therapy, the overall prognosis for patients with diabetic vasculopathy remains unsatisfactory. Angiogenesis and vascular injury and repair are associated with a variety of cells. However, the molecu...