| Literature DB >> 14690591 |
Tony R Hazbun1, Lars Malmström, Scott Anderson, Beth J Graczyk, Bethany Fox, Michael Riffle, Bryan A Sundin, J Derringer Aranda, W Hayes McDonald, Chun-Hwei Chiu, Brian E Snydsman, Phillip Bradley, Eric G D Muller, Stanley Fields, David Baker, John R Yates, Trisha N Davis.
Abstract
Interpreting genome sequences requires the functional analysis of thousands of predicted proteins, many of which are uncharacterized and without obvious homologs. To assess whether the roles of large sets of uncharacterized genes can be assigned by targeted application of a suite of technologies, we used four complementary protein-based methods to analyze a set of 100 uncharacterized but essential open reading frames (ORFs) of the yeast Saccharomyces cerevisiae. These proteins were subjected to affinity purification and mass spectrometry analysis to identify copurifying proteins, two-hybrid analysis to identify interacting proteins, fluorescence microscopy to localize the proteins, and structure prediction methodology to predict structural domains or identify remote homologies. Integration of the data assigned function to 48 ORFs using at least two of the Gene Ontology (GO) categories of biological process, molecular function, and cellular component; 77 ORFs were annotated by at least one method. This combination of technologies, coupled with annotation using GO, is a powerful approach to classifying genes.Entities:
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Year: 2003 PMID: 14690591 DOI: 10.1016/s1097-2765(03)00476-3
Source DB: PubMed Journal: Mol Cell ISSN: 1097-2765 Impact factor: 17.970