Gil Alterovitz

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Gene Ontology (GO) has been widely used to infer functional significance associated with sets of genes in order to automate discoveries within large-scale genetic studies. A level in GO's direct acyclic graph structure is often assumed to be indicative of its terms' specificities, although other work has suggested this assumption does not hold.(More)
The field of synthetic biology holds an inspiring vision for the future; it integrates computational analysis, biological data and the systems engineering paradigm in the design of new biological machines and systems. These biological machines are built from basic biomolecular components analogous to electrical devices, and the information flow among these(More)
INTRODUCTION The goal of personalised medicine in the intensive care unit (ICU) is to predict which diagnostic tests, monitoring interventions and treatments translate to improved outcomes given the variation between patients. Unfortunately, processes such as gene transcription and drug metabolism are dynamic in the critically ill; that is, information(More)
BACKGROUND Identification of expression quantitative trait loci (eQTLs) is an emerging area in genomic study. The task requires an integrated analysis of genome-wide single nucleotide polymorphism (SNP) data and gene expression data, raising a new computational challenge due to the tremendous size of data. RESULTS We develop a method to identify eQTLs.(More)
Robust electronic medical records (EMR's) have made large-scale phenome-based analysis feasible. The context-dependent phenome of a large ICU-based EMR database (MIMIC II) was explored, as a function of a clinical feature: white blood cell count (WBC). Phenome visualization led to the discovery that peak WBC in the range 15-45 K/μl was highly associated(More)
  • Yau-Hua Yu, Guang-Yuh Chiou, Pin-I Huang, Wen-Liang Lo, Chien-Ying Wang, Kai-Hsi Lu +6 others
  • 2012
Mounting evidence links cancers possessing stem-like properties with worse prognosis. Network biology with signal processing mechanics was explored here using expression profiles of a panel of tumor stem-like cells (TSLCs). The profiles were compared to their parental tumor cells (PTCs) and the human embryonic stem cells (hESCs), for the identification of(More)
Our aim was to uncover unrecognized phenomic relationships using force-based network visualization methods, based on observed electronic medical record data. A primary phenotype was defined from actual patient profiles in the Multiparameter Intelligent Monitoring in Intensive Care II database. Network visualizations depicting primary relationships were(More)