GeneCards Version 3: the human gene integrator

GeneCards (www.genecards.org) is a comprehensive, authoritative compendium of annotative information about human genes, widely used for nearly 15 years. Its gene-centric content is automatically mined and integrated from over 80 digital sources, resulting in a web-based deep-linked card for each of >73 000 human gene entries, encompassing the following categories: protein coding, pseudogene, RNA gene, genetic locus, cluster and uncategorized. We now introduce GeneCards Version 3, featuring a speedy and sophisticated search engine and a revamped, technologically enabling infrastructure, catering to the expanding needs of biomedical researchers. A key focus is on gene-set analyses, which leverage GeneCards’ unique wealth of combinatorial annotations. These include the GeneALaCart batch query facility, which tabulates user-selected annotations for multiple genes and GeneDecks, which identifies similar genes with shared annotations, and finds set-shared annotations by descriptor enrichment analysis. Such set-centric features address a host of applications, including microarray data analysis, cross-database annotation mapping and gene-disorder associations for drug targeting. We highlight the new Version 3 database architecture, its multi-faceted search engine, and its semi-automated quality assurance system. Data enhancements include an expanded visualization of gene expression patterns in normal and cancer tissues, an integrated alternative splicing pattern display, and augmented multi-source SNPs and pathways sections. GeneCards now provides direct links to gene-related research reagents such as antibodies, recombinant proteins, DNA clones and inhibitory RNAs and features gene-related drugs and compounds lists. We also portray the GeneCards Inferred Functionality Score annotation landscape tool for scoring a gene’s functional information status. Finally, we delineate examples of applications and collaborations that have benefited from the GeneCards suite

Domain-Domain Interactions Underlying Herpesvirus-Human Protein-Protein Interaction Networks

Protein-domains play an important role in mediating protein-protein interactions. Furthermore, the same domain-pairs mediate different interactions in different contexts and in various organisms, and therefore domain-pairs are considered as the building blocks of interactome networks. Here we extend these principles to the host-virus interface and find the domain-pairs that potentially mediate human-herpesvirus interactions. Notably, we find that the same domain-pairs used by other organisms for mediating their interactions underlie statistically significant fractions of human-virus protein inter-interaction networks. Our analysis shows that viral domains tend to interact with human domains that are hubs in the human domain-domain interaction network. This may enable the virus to easily interfere with a variety of mechanisms and processes involving various and different human proteins carrying the relevant hub domain. Comparative genomics analysis provides hints at a molecular mechanism by which the virus acquired some of its interacting domains from its human host

Genome-Scale Analysis of Translation Elongation with a Ribosome Flow Model

We describe the first large scale analysis of gene translation that is based on a model that takes into account the physical and dynamical nature of this process. The Ribosomal Flow Model (RFM) predicts fundamental features of the translation process, including translation rates, protein abundance levels, ribosomal densities and the relation between all these variables, better than alternative (‘non-physical’) approaches. In addition, we show that the RFM can be used for accurate inference of various other quantities including genes' initiation rates and translation costs. These quantities could not be inferred by previous predictors. We find that increasing the number of available ribosomes (or equivalently the initiation rate) increases the genomic translation rate and the mean ribosome density only up to a certain point, beyond which both saturate. Strikingly, assuming that the translation system is tuned to work at the pre-saturation point maximizes the predictive power of the model with respect to experimental data. This result suggests that in all organisms that were analyzed (from bacteria to Human), the global initiation rate is optimized to attain the pre-saturation point. The fact that similar results were not observed for heterologous genes indicates that this feature is under selection. Remarkably, the gap between the performance of the RFM and alternative predictors is strikingly large in the case of heterologous genes, testifying to the model's promising biotechnological value in predicting the abundance of heterologous proteins before expressing them in the desired host

Computational Foretelling and Experimental Implementation of the Performance of Polyacrylic Acid and Polyacrylamide Polymers as Eco-Friendly Corrosion Inhibitors for Copper in Nitric Acid

Copper is primarily used in many industrial processes, but like many other metals, it suffers from corrosion damage. Polymers are not only one of the effective corrosion inhibitors but also are environmentally friendly agents in doing so. Hence, in this paper, the efficacy of two polyelectrolyte polymers, namely poly(acrylic acid) (PAA) and polyacrylamide (PAM), as corrosion inhibitors for copper in molar nitric acid medium was explored. Chemical, electrochemical, and microscopic tools were employed in this investigation. The weight-loss study revealed that the computed inhibition efficiencies (% IEs) of both PAA and PAM increased with their concentrations but diminished with increasing HNO3 concentration and temperature. The results revealed that, at similar concentrations, the values of % IEs of PAM are slightly higher than those recorded for PAA, where these values at 298 K reached 88% and 84% in the presence of a 250 mg/L of PAM and PAA, respectively. The prominent IE% values for the tested polymers are due to their strong adsorption on the Cu surface and follow the Langmuir adsorption isoform. Thermodynamic and kinetic parameters were also calculated and discussed. The kinetics of corrosion inhibition by PAA and PAM showed a negative first-order process. The results showed also that the used polymers played as mixed-kind inhibitors with anodic priority. The mechanisms of copper corrosion in nitric acid medium and its inhibition by the tested polymers were discussed. DFT calculations and molecular dynamic (MD) modelling were used to investigate the effect of PAA and PAM molecular configuration on their anti-corrosion behavior. The results indicated that the experimental and computational study are highly consistent

Estimation de l'évapotranspiration par télédétection spatiale : Enjeux et application en Afrique sahélienne

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