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BACKGROUND It has been recognized that modular organization pervades biological complexity. Based on network analysis, 'party hubs' and 'date hubs' were proposed to understand the basic principle of module organization of biomolecular networks. However, recent study on hubs has suggested that there is no clear evidence for coexistence of 'party hubs' and(More)
With the increasingly accumulated data from high-throughput technologies, study on biomolecular networks has become one of key focuses in systems biology and bioinformatics. In particular, various types of molecular networks (e.g., protein-protein interaction (PPI) network; gene regulatory network (GRN); metabolic network (MN); gene coexpression network(More)
Aberrant expression of epidermal growth factor receptor (EGFR; ErbB1) and HER2 (ErbB2) tyrosine kinases frequently occurs in glioblastoma multiforme (GBM) patients and is considered to be associated with tumor malignancy and poor patient prognosis. In the present study, a dual EGFR and HER2 inhibitor (GW2974) was evaluated for its effects in GBM in vitro(More)
BACKGROUND Transcriptional regulation is a fundamental process in biological systems, where transcription factors (TFs) have been revealed to play crucial roles. In recent years, in addition to TFs, an increasing number of non-coding RNAs (ncRNAs) have been shown to mediate post-transcriptional processes and regulate many critical pathways in both(More)
MOTIVATION Prediction of synergistic effects of drug combinations has traditionally been relied on phenotypic response data. However, such methods cannot be used to identify molecular signaling mechanisms of synergistic drug combinations. In this article, we propose an enhanced Petri-Net (EPN) model to recognize the synergistic effects of drug combinations(More)
Recent advances in automated high-resolution fluorescence microscopy and robotic handling have made the systematic and cost effective study of diverse morphological changes within a large population of cells possible under a variety of perturbations, e.g., drugs, compounds, metal catalysts, RNA interference (RNAi). Cell population-based studies deviate from(More)
Little research has been done to address the huge opportunities that may exist to reposition existing approved or generic drugs for alternate uses in cancer therapy. In addition, there has been little work on strategies to reposition experimental cancer agents for testing in alternate settings that could shorten their clinical development time. Progress in(More)
SUMMARY Systematic studies of drug repositioning require the integration of multi-level drug data, including basic chemical information (such as SMILES), drug targets, target-related signaling pathways, clinical trial information and Food and Drug Administration (FDA)-approval information, to predict new potential indications of existing drugs. Currently(More)
Convincing epidemiological data suggest an inverse association between cancer and neurodegeneration, including Alzheimer's disease (AD). Since both AD and cancer are characterized by abnormal, but opposing cellular behavior, i.e., increased cell death in AD while excessive cell growth occurs in cancer, this motivates us to initiate the study into unraveling(More)
Transcription factors (TFs) and epigenetic modifications play crucial roles in the regulation of gene expression, and correlations between the two types of factors have been discovered. However, methods for quantitatively studying the correlations remain limited. Here, we present a computational approach to systematically investigating how epigenetic(More)