A critical assessment of Mus musculus gene function prediction using integrated genomic evidence

Background: Several years after sequencing the human genome and the mouse genome, much remains to be discovered about the functions of most human and mouse genes. Computational prediction of gene function promises to help focus limited experimental resources on the most likely hypotheses. Several algorithms using diverse genomic data have been applied to this task in model organisms; however, the performance of such approaches in mammals has not yet been evaluated. Results: In this study, a standardized collection of mouse functional genomic data was assembled; nine bioinformatics teams used this data set to independently train classifiers and generate predictions of function, as defined by Gene Ontology (GO) terms, for 21,603 mouse genes; and the best performing submissions were combined in a single set of predictions. We identified strengths and weaknesses of current functional genomic data sets and compared the performance of function prediction algorithms. This analysis inferred functions for 76% of mouse genes, including 5,000 currently uncharacterized genes. At a recall rate of 20%, a unified set of predictions averaged 41% precision, with 26% of GO terms achieving a precision better than 90%. Conclusion: We performed a systematic evaluation of diverse, independently developed computational approaches for predicting gene function from heterogeneous data sources in mammals. The results show that currently available data for mammals allows predictions with both breadth and accuracy. Importantly, many highly novel predictions emerge for the 38% of mouse genes that remain uncharacterized

A Genome-Wide Gene Function Prediction Resource for Drosophila melanogaster

Predicting gene functions by integrating large-scale biological data remains a challenge for systems biology. Here we present a resource for Drosophila melanogaster gene function predictions. We trained function-specific classifiers to optimize the influence of different biological datasets for each functional category. Our model predicted GO terms and KEGG pathway memberships for Drosophila melanogaster genes with high accuracy, as affirmed by cross-validation, supporting literature evidence, and large-scale RNAi screens. The resulting resource of prioritized associations between Drosophila genes and their potential functions offers a guide for experimental investigations

Effect of ageing on the microstructural evolution in a new design of maraging steels with carbon

A new maraging steel, based on carbide precipitation, is described. Two alloys were designed namely Fe-10Mn-0.25C-2Cr-1Mo wt% (2CrMo) and Fe-10Mn-0.25C-1Cr-2Mo wt% (Cr2Mo). These compositions were chosen to achieve ultra-high strength and high tensile elongation; the former and latter are promoted through the simulatenous precipitation of Cr- and Mo-rich carbides and Mn-rich reverted austenite. The alloys were manufactured through the standard melting, casting and hot working route. Following a solution treatment at 870 °C and quench, which gave a fully martensitic structure, the alloys were aged for various times at 510 °C. The microstructure and tensile properties were investigated in detail as a function of ageing time. The microstructure observed was dominated by micron scale and nanometre scale Mn segregation which determined the local Ac3 temperature. Austenite reversion occurred in both alloys, peaking at 16 h in both cases. In the 2CrMo alloy, the reverted austenite was mainly globular in morphology due the Ac3 temperature being lower than the ageing temperature, but was acicular in the Cr2Mo with Ac3 similar to the ageing temperature of 510 °C. Moreover, acicular austenite was promoted by Mn segregation at martensite lath boundaries in Cr2Mo. In the 2CrMo steel, carbide precipitation (M3C and M7C3) occurred during heating to the ageing temperature, but the carbides gradually dissolved with further ageing. In contrast, in the Cr2Mo alloy, precipitation of carbides (M7C3 and M2C) occurred during ageing, the volume fraction of which increased with ageing time. In both alloys a TRIP effect was observed, but the extent of this was greater for the Cr2Mo alloy. The complex microstructure obtained after 16 h led to an excellent combination of strength of 1.3 GPa and elongation of 18%. Physics-based models for the microstructure in martensite, precipitation kinetics, as well as for TRIP in austenite were employed to explain and predict the individual strengthtening contributions of the microstructure to the total strength, confirming that the maximum strength-elongation relationship found after 16 h is due to an optimal combination of a slightly overaged - but still strong- martensite and 30% of reverted austenite, for increased work hardening and ductility