Gene function prediction from synthetic lethality networks via ranking on demand.

MOTIVATION: Synthetic lethal interactions represent pairs of genes whose individual mutations are not lethal, while the double mutation of both genes does incur lethality. Several studies have shown a correlation between functional similarity of genes and their distances in networks based on synthetic lethal interactions. However, there is a lack of algorithms for predicting gene function from synthetic lethality interaction networks. RESULTS: In this article, we present a novel technique called kernelROD for gene function prediction from synthetic lethal interaction networks based on kernel machines. We apply our novel algorithm to Gene Ontology functional annotation prediction in yeast. Our experiments show that our method leads to improved gene function prediction compared with state-of-the-art competitors and that combining genetic and congruence networks leads to a further improvement in prediction accuracy.

Sex ratio of the false trevaly Lactarius lactarius (Bloch and Schneider)

The sex ratio in Lactarius lactarius at different months and years was studied. Sex ratio data show that males outnumber females in all months except in October. The insignificant difference in the number of individuals of both the sexes during spawning months (January, March, October and November) indicated that males and females congregate during the spawning season. Among the larger specimens, males constituted the minority.