Efficient hepatitis C virus particle formation requires diacylglycerol acyltransferase-1.

Hepatitis C virus (HCV) infection is closely tied to the lipid metabolism of liver cells. Here we identify the triglyceride-synthesizing enzyme diacylglycerol acyltransferase-1 (DGAT1) as a key host factor for HCV infection. DGAT1 interacts with the viral nucleocapsid core and is required for the trafficking of core to lipid droplets. Inhibition of DGAT1 activity or RNAi-mediated knockdown of DGAT1 severely impairs infectious virion production, implicating DGAT1 as a new target for antiviral therapy

swissPIT: a novel approach for pipelined analysis of mass spectrometry data

The identification and characterization of peptides from tandem mass spectrometry (MS/MS) data represents a critical aspect of proteomics. Today, tandem MS analysis is often performed by only using a single identification program achieving identification rates between 10-50% (Elias and Gygi, 2007). Beside the development of new analysis tools, recent publications describe also the pipelining of different search programs to increase the identification rate (Hartler et al., 2007; Keller et al., 2005). The Swiss Protein Identification Toolbox (swissPIT) follows this approach, but goes a step further by providing the user an expandable multi-tool platform capable of executing workflows to analyze tandem MS-based data. One of the major problems in proteomics is the absent of standardized workflows to analyze the produced data. This includes the pre-processing part as well as the final identification of peptides and proteins. The main idea of swissPIT is not only the usage of different identification tool in parallel, but also the meaningful concatenation of different identification strategies at the same time. The swissPIT is open source software but we also provide a user-friendly web platform, which demonstrates the capabilities of our software and which is available at http://swisspit.cscs.ch upon request for account. Contact: [email protected]

Toxicity of Tamoxifen on Daphnia pulex

Daphnia pulex is a water flea considered an environmental indicator species. In this experiment we exposed Daphnia to Tamoxifen in low or high concentrations, dissolved in dimethyl sulfoxide with water, and we measured the amount of proteins at day 2 and 7. With the R package maSigPro we selected proteins changing significantly over time among the four experimental groups and we developed a cluster analysis for the behavior of profiles over time, to understand which and how these specific proteins change according to the treatment received. The information obtained from this study represents an important first step towards characterizing patterns specific to environmental contaminants

Qualitative Simulation of Genetic Regulatory Networks Using Piecewise-Linear Models

In order to cope with the large amounts of data that have become available in genomics, mathematical tools for the analysis of networks of interactions between genes, proteins, and other molecules are indispensable. We present a method for the qualitative simulation of genetic regulatory networks, based on a class of piecewise-linear (PL) differential equations that has been well-studied in mathematical biology. The simulation method is well-adapted to state-of-the-art measurement techniques in genomics which often provide qualitative and coarse-grained descriptions of genetic regulatory networks. The method is able to deal with nontrivial mathematical problems induced by the discontinuous right-hand sides of the differential equations. Furthermore, it guarantees that the simulation covers all possible solutions of quantitative PL models corresponding to the qualitative PL model used by the method. The qualitative simulation method has been implemented in Java

Genetic Network Analyzer: A Tool for the Qualitative Simulation of Genetic Regulatory Networks

The study of genetic regulatory networks has received a major impetus from the recent development of experimental techniques allowing the measuremen- t of spatiotemporal patterns of gene expression in a massively parallel way. This progress of experimental methods calls for the development of appropriate computer tools for the modeling and simulation of gene regulation processes. These tools should be able to deal with two major difficulties hampering modeling and simulation studies, viz. incomplete knowledge of the biochemical reaction mechanisms and the absence of quantitative informatio- n on kinetic parameters and molecular concentrations. We present a computer tool for the modeling and simulation of genetic regulatory networks, called Genetic Network Analyzer (GNA). The tool is based on a qualitative simulation method that employs coarse-grained models of regulatory networks. The use of GNA is illustrated in a study of the network of genes and interactions regulating the initiation of sporulation in Bacillus subtilis

Logical Modeling and Analysis of Cellular Regulatory Networks With GINsim 3.0

The logical formalism is well adapted to model large cellular networks, in particular when detailed kinetic data are scarce. This tutorial focuses on this well-established qualitative framework. Relying on GINsim (release 3.0), a software implementing this formalism, we guide the reader step by step toward the definition, the analysis and the simulation of a four-node model of the mammalian p53-Mdm2 network

Robustness of kappa (κ) measurement in low-to-moderate seismicity 1 areas: insight from a site-specific study in Provence, France

International audienc

ExPASy: SIB bioinformatics resource portal

ExPASy (http://www.expasy.org) has worldwide reputation as one of the main bioinformatics resources for proteomics. It has now evolved, becoming an extensible and integrative portal accessing many scientific resources, databases and software tools in different areas of life sciences. Scientists can henceforth access seamlessly a wide range of resources in many different domains, such as proteomics, genomics, phylogeny/evolution, systems biology, population genetics, transcriptomics, etc. The individual resources (databases, web-based and downloadable software tools) are hosted in a ‘decentralized' way by different groups of the SIB Swiss Institute of Bioinformatics and partner institutions. Specifically, a single web portal provides a common entry point to a wide range of resources developed and operated by different SIB groups and external institutions. The portal features a search function across ‘selected' resources. Additionally, the availability and usage of resources are monitored. The portal is aimed for both expert users and people who are not familiar with a specific domain in life sciences. The new web interface provides, in particular, visual guidance for newcomers to ExPAS