BioCAD: an information fusion platform for bio-network inference and analysis

Background : As systems biology has begun to draw growing attention, bio-network inference and analysis have become more and more important. Though there have been many efforts for bio-network inference, they are still far from practical applications due to too many false inferences and lack of comprehensible interpretation in the biological viewpoints. In order for applying to real problems, they should provide effective inference, reliable validation, rational elucidation, and sufficient extensibility to incorporate various relevant information sources. Results : We have been developing an information fusion software platform called BioCAD. It is utilizing both of local and global optimization for bio-network inference, text mining techniques for network validation and annotation, and Web services-based workflow techniques. In addition, it includes an effective technique to elucidate network edges by integrating various information sources. This paper presents the architecture of BioCAD and essential modules for bio-network inference and analysis. Conclusion : BioCAD provides a convenient infrastructure for network inference and network analysis. It automates series of users' processes by providing data preprocessing tools for various formats of data. It also helps inferring more accurate and reliable bio-networks by providing network inference tools which utilize information from distinct sources. And it can be used to analyze and validate the inferred bio-networks using information fusion tools.ope

Prefrontal grey-matter changes in short-term and long-term abstinent methamphetamine abusers

Journal ArticleAuthor's explored grey-matter density in 29 methamphetamine abusers and 20 healthy comparison subjects using voxel-based morphometry. Grey-matter density changes and performances on the Wisconsin Card Sorting test (WCST) were also compared between 11 short-term (<6 months) and 18 long-term (o6 months) abstinent methamphetamine abusers. Methamphetamine abusers had lower grey-matter density in the right middle frontal cortex (corrected p<0.05) and more total errors in the WCST (p<0.01) relative to healthy comparison subjects. Grey-matter density decrease in the right middle frontal cortex correlated with total errors in the WCST in methamphetamine abusers (r=x0.45). Long-term abstinent abusers had significantly less right middle frontal grey-matter density decrease (p<0.01) and total errors in the WCST (p<0.01) than short-term abstinent abusers, but more than the healthy comparison subjects. We report that methamphetamine abusers have prefrontal grey-matter deficit, which may, in part, recover with long-term abstinence

Novel function of C5 protein as a metabolic stabilizer of M1 RNA

AbstractEscherichia coli RNase P is a ribonucleoprotein composed of a large RNA subunit (M1 RNA) and a small protein subunit (C5 protein). We examined if C5 protein plays a role in maintaining metabolic stability of M1 RNA. The sequestration of C5 protein available for M1 RNA binding reduced M1 RNA stability in vivo, and its reduced stability was recovered via overexpression of C5 protein. In addition, M1 RNA was rapidly degraded in a temperature-sensitive C5 protein mutant strain at non-permissive temperatures. Collectively, our results demonstrate that the C5 protein metabolically stabilizes M1 RNA in the cell