ArticleNature methods2006
A pooling-deconvolution strategy for biological network elucidation.
Article in Nature methods, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- A small-molecule VHL molecular glue degrader for cysteine dioxygenase 1.Nature chemical biology · 2025Article
- A colony multiplex quantitative PCR-Based 3S3DBC method and variations of it for screening DNA libraries.PloS one · 2015Article
- The mammalian proteins MMS19, MIP18, and ANT2 are involved in cytoplasmic iron-sulfur cluster protein assembly.The Journal of biological chemistry · 2012Article
- Diversity in genetic in vivo methods for protein-protein interaction studies: from the yeast two-hybrid system to the mammalian split-luciferase system.Microbiology and molecular biology reviews : MMBR · 2012Review
- Article
- Compressed Genotyping.IEEE transactions on information theory · 2010Article
- Shifted Transversal Design smart-pooling for high coverage interactome mapping.Genome research · 2009Article
- Protein kinase substrate identification on functional protein arrays.BMC biotechnology · 2008Article
- A yeast two-hybrid smart-pool-array system for protein-interaction mapping.Nature methods · 2007Article
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Abstract
The generation of large-scale data sets is a fundamental requirement of systems biology. But despite recent advances, generation of such high-coverage data remains a major challenge. We developed a pooling-deconvolution strategy that can dramatically decrease the effort required. This strategy, pooling with imaginary tags followed by deconvolution (PI-deconvolution), allows the screening of 2(n) probe proteins (baits) in 2 x n pools, with n replicates for each bait. Deconvolution of baits with their binding partners (preys) can be achieved by reading the prey's profile from the 2 x n experiments. We validated this strategy for protein-protein interaction mapping using both proteome microarrays and a yeast two-hybrid array, demonstrating that PI-deconvolution can be used to identify interactions accurately with fewer experiments and better coverage. We also show that PI-deconvolution can be used to identify protein-small molecule interactions inferred from profiling the yeast deletion collection. PI-deconvolution should be applicable to a wide range of library-against-library approaches and can also be used to optimize array designs.
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