Inferring gene networks: dream or nightmare?

We describe several algorithms with winning performance in the Dialogue for Reverse Engineering Assessments and Methods (DREAM2) Reverse Engineering Competition 2007. After the gold standards for the challenges were released, the performance of the algorithms could be thoroughly evaluated under different parameters or alternative ways of solving systems of equations. For the analysis of Challenge 4, the "In-silico" challenges, we employed methods to explicitly deal with perturbation data and time-series data. We show that original methods used to produce winning submissions could easily be altered to substantially improve performance. For Challenge 5, the genome-scale Escherichia coli network, we evaluated a variety of measures of association. These data are troublesome, and no good solutions could be produced, either by us or by any other teams. Our best results were obtained when analyzing subdatasets instead of considering the dataset as a whole.

Protein networking: insights into global functional organization of proteomes.

The formulation of network models from global protein studies is essential to understand the functioning of organisms. Network models of the proteome enable the application of Complex Network Analysis, a quantitative framework to investigate large complex networks using techniques from graph theory, statistical physics, dynamical systems and other fields. This approach has provided many insights into the functional organization of the proteome so far and will likely continue to do so. Currently, several network concepts have emerged in the field of proteomics. It is important to highlight the differences between these concepts, since different representations allow different insights into functional organization. One such concept is the protein interaction network, which contains proteins as nodes and undirected edges representing the occurrence of binding in large-scale protein-protein interaction studies. A second concept is the protein-signaling network, in which the nodes correspond to levels of post-translationally modified forms of proteins and directed edges to causal effects through post-translational modification, such as phosphorylation. Several other network concepts were introduced for proteomics. Although all formulated as networks, the concepts represent widely different physical systems. Therefore caution should be taken when applying relevant topological analysis. We review recent literature formulating and analyzing such networks.

High resolution analysis and phylogenetic network construction using complete mtDNA sequences in sardinian genetic isolates.

For mitochondrial phylogenetic analysis, the best result comes from complete sequences. We therefore decided to sequence the entire mitochondrial DNA (mtDNA) (coding and D-loop regions) of 63 individuals selected in 3 small Ogliastra villages, an isolated area of eastern Sardinia: Talana, Urzulei, and Perdasdefogu. We studied at least one individual for each of the most frequent maternal genealogical lineages belonging to haplogroups H, V, J, K, T, U, and X. We found in our 63 samples, 172 and 69 sequence changes in the coding and in the D-loop region, respectively. Thirteen out of 172 sequence changes in the coding region are novel. It is our hypothesis that some of them are characteristic of the Ogliastra region and/or Sardinia. We reconstructed the phylogenetic network of the 63 complete mtDNA sequences for the 3 villages. We also drew a network including a large number of European sequences and calculated various indices of genetic diversity in Ogliastra. It appears that these small populations remained extremely isolated and genetically differentiated compared with other European populations. We also identified in our samples a never previously described subhaplogroup, U5b3, which seems peculiar to the Ogliastra region.

Browsing isolated population data.

BACKGROUND: In our studies of genetically isolated populations in a remote mountain area in the center of Sardinia (Italy), we found that 80-85% of the inhabitants of each village belong to a single huge pedigree with families strictly connected to each other through hundreds of loops. Moreover, intermarriages between villages join pedigrees of different villages through links that make family trees even more complicated. Unfortunately, none of the commonly used pedigree drawing tools are able to draw the complete pedigree, whereas it is commonly accepted that the visual representation of families is very important as it helps researchers in identifying clusters of inherited traits and genotypes. We had a representation issue that compels researchers to work with subsets extracted from the overall genealogy, causing a serious loss of information on familiar relationships. To visually explore such complex pedigrees, we developed PedNavigator, a browser for genealogical databases properly suited for genetic studies. RESULTS: The PedNavigator is useful for genealogical research due to its capacity to represent family relations between persons and to make a visual verification of the links during family history reconstruction. As for genetic studies, it is helpful to follow propagation of a specific set of genetic markers (haplotype), or to select people for linkage analysis, showing relations between various branch of a family tree of affected subjects. AVAILABILITY: PedNavigator is an application integrated into a Framework designed to handle data for human genetic studies based on the Oracle platform. To allow the use of PedNavigator also to people not owning the same required informatics infrastructure or systems, we developed PedNavigator Lite with mainly the same features of the integrated one, based on MySQL database server. This version is free for academic users, and it is available for download from our site http://www.shardna.com.

A hybrid genetic-neural system for predicting protein secondary structure.

BACKGROUND: Due to the strict relation between protein function and structure, the prediction of protein 3D-structure has become one of the most important tasks in bioinformatics and proteomics. In fact, notwithstanding the increase of experimental data on protein structures available in public databases, the gap between known sequences and known tertiary structures is constantly increasing. The need for automatic methods has brought the development of several prediction and modelling tools, but a general methodology able to solve the problem has not yet been devised, and most methodologies concentrate on the simplified task of predicting secondary structure. RESULTS: In this paper we concentrate on the problem of predicting secondary structures by adopting a technology based on multiple experts. The system performs an overall processing based on two main steps: first, a "sequence-to-structure" prediction is enforced by resorting to a population of hybrid (genetic-neural) experts, and then a "structure-to-structure" prediction is performed by resorting to an artificial neural network. Experiments, performed on sequences taken from well-known protein databases, allowed to reach an accuracy of about 76%, which is comparable to those obtained by state-of-the-art predictors. CONCLUSION: The adoption of a hybrid technique, which encompasses genetic and neural technologies, has demonstrated to be a promising approach in the task of protein secondary structure prediction.

PedNavigator: a pedigree drawing servlet for large and inbred populations.

PedNavigator is a pedigree drawing application for large and complex pedigrees. It has been developed especially for genetic and epidemiological studies of isolated populations characterized by high inbreeding and multiple matrimonies. PedNavigator is written in Java and is intended as a server-side web application, allowing researchers to 'walk' through family ties by point-and-clicking on person's symbols. The application is able to enrich the pedigree drawings with genotypic and phenotypic information taken from the underlying relational database.