7 research outputs found
Evaluating Ortholog Prediction Algorithms in a Yeast Model Clade
RSD, respectively, so that
they can predict orthologs across multiple taxa) against a set of 2,723
groups of high-quality curated orthologs from 6 Saccharomycete yeasts in the
Yeast Gene Order Browser. of all algorithms dramatically increased in these traps.) for evolutionary and functional
genomics studies where the objective is the accurate inference of
single-copy orthologs (e.g., molecular phylogenetics), but that all
algorithms fail to accurately predict orthologs when paralogy is
rampant
Algorithm of OMA for large-scale orthology inference
Since the publication of our article (Roth, Gonnet, and Dessimoz: BMC Bioinformatics 2008 9: 518), we have noticed several errors, which we correct in the following
Local Function Conservation in Sequence and Structure Space
We assess the variability of protein function in protein sequence and structure space. Various regions in this space exhibit considerable difference in the local conservation of molecular function. We analyze and capture local function conservation by means of logistic curves. Based on this analysis, we propose a method for predicting molecular function of a query protein with known structure but unknown function. The prediction method is rigorously assessed and compared with a previously published function predictor. Furthermore, we apply the method to 500 functionally unannotated PDB structures and discuss selected examples. The proposed approach provides a simple yet consistent statistical model for the complex relations between protein sequence, structure, and function. The GOdot method is available online (http://godot.bioinf.mpi-inf.mpg.de)
Three-Level Prediction of Protein Function by Combining Profile-Sequence Search, Profile-Profile Search, and Domain Co-Occurrence Networks
Inferring Orthology and Paralogy.
The distinction between orthologs and paralogs, genes that started diverging by speciation versus duplication, is relevant in a wide range of contexts, most notably phylogenetic tree inference and protein function annotation. In this chapter, we provide an overview of the methods used to infer orthology and paralogy. We survey both graph-based approaches (and their various grouping strategies) and tree-based approaches, which solve the more general problem of gene/species tree reconciliation. We discuss conceptual differences among the various orthology inference methods and databases and examine the difficult issue of verifying and benchmarking orthology predictions. Finally, we review typical applications of orthologous genes, groups, and reconciled trees and conclude with thoughts on future methodological developments