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Single molecular functional network construction and analysis of disease is very useful to identify novel and potential targets for prognosis and therapy. This paper integrated an infer method based on linear programming and decomposition procedure with function analysis using Kappa statistics and fuzzy heuristic cluster (DAVID). We first identified the significant molecule OAS1, then constructed OAS1 up- and down-stream network by infer and further data-mined the main OAS1 modules including response to stimulus, catalytic activity, organelle, metabolic process, alternative splicing and sequence variant from 16 frontal cortex of HIV encephalitis (HIVE) and 12 no-encephalitis HIV patients in the same GEO Dataset GDS1726. Our infer OAS1 network result showed the different gene rate of HIVE as 78% (21/27) compared with the control considering activation and inhibition relationship. The different active genes in HIVE include HLA_B, ISG15_1, ISG15_2, LCAT, LY96, M33210, PDCD4, STAT1, VEZF1, ADH1B, DGKG, IFI35, LSM7, TSPAN4, ZC3HAV1 and the different inhibitory genes include DGKG, CREB5, GAS1, M33210, TENC1, VEZF1. Our integrative analysis showed the positive results of OAS1 response to stimulus, catalytic activity, organelle, metabolic process, alternative splicing and sequence variant through the net numbers of activation minus inhibition compared with the control and predicted the increases of these modules in HIVE. |
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Keywords:OAS1; network construction and analysis; the frontal cortex with HIVE; integrative biocomputation |
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