Definition of valid proteomic biomarkers: a bayesian solution

Clinical proteomics is suffering from high hopes generated by reports on apparent biomarkers, most of which could not be later substantiated via validation. This has brought into focus the need for improved methods of finding a panel of clearly defined biomarkers. To examine this problem, urinary proteome data was collected from healthy adult males and females, and analysed to find biomarkers that differentiated between genders. We believe that models that incorporate sparsity in terms of variables are desirable for biomarker selection, as proteomics data typically contains a huge number of variables (peptides) and few samples making the selection process potentially unstable. This suggests the application of a two-level hierarchical Bayesian probit regression model for variable selection which assumes a prior that favours sparseness. The classification performance of this method is shown to improve that of the Probabilistic K-Nearest Neighbour model

RNA Interference: Its Use as Antiviral Therapy

RNA interference (RNAi) is a sequence-specific gene-silencing mechanism that has been proposed to function as a defence mechanism of eukaryotic cells against viruses and transposons. RNAi was first observed in plants in the form of a mysterious immune response to viral pathogens. But RNAi is more than just a response to exogenous genetic material. Small RNAs termed microRNA (miRNA) regulate cellular gene expression programs to control diverse steps in cell development and physiology. The discovery that exogenously delivered short interfering RNA (siRNA) can trigger RNAi in mammalian cells has made it into a powerful technique for generating genetic knock-outs. It also raises the possibility to use RNAi technology as a therapeutic tool against pathogenic viruses. Indeed, inhibition of virus replication has been reported for several human pathogens including human immunodeficiency virus, the hepatitis B and C viruses and influenza virus. We reviewed the field of antiviral RNAi research in 2003 (Haasnoot et al. 2003), but many new studies have recently been published. In this review, we present a complete listing of all antiviral strategies published up to and including December 2004. The latest developments in the RNAi field and their antiviral application are describe