Journal Article10.1016/J.YMBEN.2010.07.001
Network-based function prediction and interactomics: the case for metabolic enzymes.
TL;DR: The state of the art in network-based function prediction is reviewed, which can be used to unravel the functions of the uncharacterized proteins accumulating in the genomic databases and some of the underlying difficulties and successes are described.
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About: This article is published in Metabolic Engineering. The article was published on 01 Jan 2011. The article focuses on the topics: Protein function prediction.
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Citations
The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored
Damian Szklarczyk,Andrea Franceschini,Michael Kuhn,Milan Simonovic,Alexander Roth,Pablo Minguez,Tobias Doerks,Manuel Stark,Jean Muller,Peer Bork,Lars Juhl Jensen,Christian von Mering +11 more
TL;DR: An update on the online database resource Search Tool for the Retrieval of Interacting Genes (STRING), which provides uniquely comprehensive coverage and ease of access to both experimental as well as predicted interaction information.
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Exploiting indirect neighbours and topological weight to predict protein function from protein-protein interactions
Hon Nian Chua,Wing-Kin Sung,Limsoon Wong +2 more
- 09 Apr 2006
TL;DR: An algorithm is developed that predicts the functions of a protein in two steps: assigning a weight to each of its level-1 and level-2 neighbours by estimating its functional similarity with the protein using the local topology of the interaction network as well as the reliability of experimental sources and scoring each function based on its weighted frequency in these neighbours.
Towards revealing the functions of all genes in plants
Seung Y. Rhee,Marek Mutwil +1 more
TL;DR: This review of computational and statistical approaches and omics data used for inferring gene function in plants, with an emphasis on network-based inference, notes the current limitations and possible future directions.
246
Elucidating gene function and function evolution through comparison of co-expression networks of plants.
TL;DR: It is hypothesized that in comparison to simple co-expression analysis, comparative analysis would yield more accurate gene function predictions, and a possible composition of cellulose biosynthesis machinery during earlier stages of plant evolution is proposed.
Genome scale engineering techniques for metabolic engineering
TL;DR: This review will attempt to summarize recent genome-scale design, build, test, and learn technologies and relate their use to a range of metabolic engineering applications.
66
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