However, evaluating their performance is unfeasible unless a ‘gol

However, evaluating their performance is unfeasible unless a ‘gold standard’ is available to measure how close the reconstructed

network is to the ground truth. One measure of this is the stability of these predictions to data resampling approaches. We introduce NetSI, a family of Network Stability Indicators, to assess quantitatively the stability of a reconstructed network in terms of inference variability selleck screening library due to data subsampling. In order to evaluate network stability, the main NetSI methods use a global/local network metric in combination with a resampling (bootstrap or cross-validation) procedure. In addition, we provide two normalized variability scores over data resampling to measure edge weight stability and node degree stability, and then introduce a stability ranking for edges and nodes. A complete implementation of the NetSI indicators, including the Hamming-Ipsen-Mikhailov (HIM) network distance adopted in this paper is available with the R package

nettools. We demonstrate the use of the NetSI family by measuring network stability on four datasets against alternative network reconstruction methods. First, the effect of sample size on stability of inferred networks is studied in a gold standard framework on yeast-like data from the Gene Net Weaver simulator. We also consider the impact of varying Cell Cycle inhibitor modularity on a set of structurally different networks (50 nodes,

from 2 to 10 modules), and then of complex feature covariance structure, showing the different behaviours of standard reconstruction methods based on Pearson correlation, Maximum Information Coefficient (MIC) and False Discovery Rate (FDR) Selleckchem Dorsomorphin strategy. Finally, we demonstrate a strong combined effect of different reconstruction methods and phenotype subgroups on a hepatocellular carcinoma miRNA microarray dataset (240 subjects), and we validate the analysis on a second dataset (166 subjects) with good reproducibility.”
“The pro-apoptotic effects of hydrogen peroxide and the purported anti-apoptotic effects of Vitamin C on chicken embryonic fibroblasts were investigated. Hydrogen peroxide induced morphological changes in a dose dependent manner, and a myriad of autophagosomes were observed using transmission electron microscopy. Doxorubicin elicited alterations were not inhibited by co-incubation with Vitamin C except that mitochondrial structure was slightly improved. TUNEL assay, cytotoxicity analysis and flow cytometry revealed that the cytotoxicity, DNA fragmentation and apoptotic rates were dose dependent upon treatment with hydrogen peroxide. Calcium homeostasis was disrupted in a dose dependent manner, and cell cycle was blocked at G(2)/M checkpoint at low concentration and S/G(2) checkpoint at high concentration respectively upon treatment with hydrogen peroxide.

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