computational identification of transcriptional regulators in human endotoxemia计算转录监管机构在人体内毒素的识别.pdfVIP

Computational Identification of Transcriptional Regulators in Human Endotoxemia 1 2 3 3 Tung T. Nguyen , Panagiota T. Foteinou , Steven E. Calvano , Stephen F. Lowry , Ioannis P. Androulakis2,3* 1 BioMaPS Institute for Quantitative Biology, Rutgers University, Piscataway, New Jersey, United States of America, 2 Department of Biomedical Engineering, Rutgers University, Piscataway, New Jersey, United States of America, 3 Department of Surgery, Robert Wood Johnson Medical School, University of Medicine and Dentistry, New Jersey, New Brunswick, New Jersey, United States of America Abstract One of the great challenges in the post-genomic era is to decipher the underlying principles governing the dynamics of biological responses. As modulating gene expression levels is among the key regulatory responses of an organism to changes in its environment, identifying biologically relevant transcriptional regulators and their putative regulatory interactions with target genes is an essential step towards studying the complex dynamics of transcriptional regulation. We present an analysis that integrates various computational and biological aspects to explore the transcriptional regulation of systemic inflammatory responses through a human endotoxemia model. Given a high-dimensional transcriptional profiling dataset from human blood leukocytes, an elementary set of temporal dynamic responses which capture the essence of a pro-inflammatory phase, a counter-regulatory response and a dysregulation in leukocyte bioenergetics has been extracted. Upon identification of these expression patterns, fourteen inflammation-specific gene batteries that represent groups of hypothetically ‘coregulated’ genes are proposed. Subsequently,