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SUMMARY QTLNetwork is a software package for mapping and visualizing the genetic architecture underlying complex traits for experimental populations derived from a cross between two inbred lines. It can simultaneously map quantitative trait loci (QTL) with individual effects, epistasis and QTL-environment interaction. Currently, it is able to handle data(More)
SUMMARY Understanding how interactions among set of genes affect diverse phenotypes is having a greater impact on biomedical research, agriculture and evolutionary biology. Mapping and characterizing the isolated effects of single quantitative trait locus (QTL) is a first step, but we also need to assemble networks of QTLs and define non-additive(More)
The determination of gene-by-gene and gene-by-environment interactions has long been one of the greatest challenges in genetics. The traditional methods are typically inadequate because of the problem referred to as the "curse of dimensionality." Recent combinatorial approaches, such as the multifactor dimensionality reduction (MDR) method, the(More)
A key goal of biology is to construct networks that predict complex system behavior. We combine multiple types of molecular data, including genotypic, expression, transcription factor binding site (TFBS), and protein-protein interaction (PPI) data previously generated from a number of yeast experiments, in order to reconstruct causal gene networks. Networks(More)
A key goal of biomedical research is to elucidate the complex network of gene interactions underlying complex traits such as common human diseases. Here we detail a multistep procedure for identifying potential key drivers of complex traits that integrates DNA-variation and gene-expression data with other complex trait data in segregating mouse populations.(More)
In acute promyelocytic leukaemia (APL), arsenic trioxide induces degradation of the fusion protein encoded by the PML-RARA oncogene, differentiation of leukaemic cells and produces clinical remissions. SUMOylation of its PML moiety was previously implicated, but the nature of the degradation pathway involved and the role of PML-RARalpha catabolism in the(More)
Supervised topic models utilize document's side information for discovering predictive low dimensional representations of documents; and existing models apply likelihood-based estimation. In this paper, we present a max-margin supervised topic model for both continuous and categorical response variables. Our approach, the maximum entropy discrimination(More)
In Arabidopsis, the tapetum plays important roles in anther development by providing enzymes for callose dissolution and materials for pollen-wall formation, and by supplying nutrients for pollen development. Here, we report the identification and characterization of a male-sterile mutant, defective in tapetal development and function 1 (tdf1), that(More)
Methods were developed for predicting two kinds of superior genotypes (superior line and superior hybrid) based on quantative trait locus (QTL) effects including epistatic and QTL x environment interaction effects. Formulae were derived for predicting the total genetic effect of any individual with known QTLs genotype derived from the mapping population in(More)
A supervised topic model can use side information such as ratings or labels associated with documents or images to discover more predictive low dimensional topical representations of the data. However, existing supervised topic models predominantly employ likelihood-driven objective functions for learning and inference, leaving the popular and potentially(More)