Duncan P. Brown

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Function prediction by homology is widely used to provide preliminary functional annotations for genes for which experimental evidence of function is unavailable or limited. This approach has been shown to be prone to systematic error, including percolation of annotation errors through sequence databases. Phylogenomic analysis avoids these errors in(More)
The Berkeley Phylogenomics Group presents PhyloFacts, a structural phylogenomic encyclopedia containing almost 10,000 'books' for protein families and domains, with pre-calculated structural, functional and evolutionary analyses. PhyloFacts enables biologists to avoid the systematic errors associated with function prediction by homology through the(More)
The Arabidopsis Ler-RPP27 gene confers AtSgt1b-independent resistance to downy mildew (Peronospora parasitica) isolate Hiks1. The RPP27 locus was mapped to a four-bacterial artificial chromosome interval on chromosome 1 from genetic analysis of a cross between the enhanced susceptibility mutant Col-edm1 (Col-sgt1) and Landsberg erecta (Ler-0). A Cf-like(More)
P hylogenomic inference of protein (or gene) function attempts to address the question, ''What function does this protein perform?'' in an evolutionary context. As originally outlined by Jonathan Eisen [1–3], phylogenomic inference of protein function is a multistep process involving selection of homologs, multiple sequence alignment (MSA), and phylogenetic(More)
BACKGROUND Function prediction by transfer of annotation from the top database hit in a homology search has been shown to be prone to systematic error. Phylogenomic analysis reduces these errors by inferring protein function within the evolutionary context of the entire family. However, accuracy of function prediction for multi-domain proteins depends on(More)
MOTIVATION Automatic clustering of protein sequences is an important problem in computational biology. The recent explosion in genome sequences has given biological researchers a vast number of novel protein sequences. However, the majority of these sequences have no experimental evidence for their molecular function in the cell, and the responsibility for(More)
The limitations of homology-based methods for prediction of protein molecular function are well known; differences in domain structure, gene duplication events and errors in existing database annotations complicate this process. In this paper we present a method to detect and model protein subfamilies, which can be used in high-throughput, genome-scale(More)
Background: Function prediction by transfer of annotation from the top database hit in a homology search has been shown to be prone to systematic error. Phylogenomic analysis reduces these errors by inferring protein function within the evolutionary context of the entire family. However, accuracy of function prediction for multi-domain proteins depends on(More)
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