Literature DB >> 32103267

Predicted Drosophila Interactome Resource and web tool for functional interpretation of differentially expressed genes.

Xiao-Bao Ding1, Jie Jin1, Yu-Tian Tao1, Wen-Ping Guo1, Li Ruan1, Qiao-Lei Yang2, Peng-Cheng Chen2, Heng Yao2, Hai-Bo Zhang1, Xin Chen1,2,3.   

Abstract

Drosophila melanogaster is a well-established model organism that is widely used in genetic studies. This species enjoys the availability of a wide range of research tools, well-annotated reference databases and highly similar gene circuitry to other insects. To facilitate molecular mechanism studies in Drosophila, we present the Predicted Drosophila Interactome Resource (PDIR), a database of high-quality predicted functional gene interactions. These interactions were inferred from evidence in 10 public databases providing information for functional gene interactions from diverse perspectives. The current version of PDIR includes 102 835 putative functional associations with balanced sensitivity and specificity, which are expected to cover 22.56% of all Drosophila protein interactions. This set of functional interactions is a good reference for hypothesis formulation in molecular mechanism studies. At the same time, these interactions also serve as a high-quality reference interactome for gene set linkage analysis (GSLA), which is a web tool for the interpretation of the potential functional impacts of a set of changed genes observed in transcriptomics analyses. In a case study, we show that the PDIR/GSLA system was able to produce a more comprehensive and concise interpretation of the collective functional impact of multiple simultaneously changed genes compared with the widely used gene set annotation tools, including PANTHER and David. PDIR and its associated GSLA service can be accessed at http://drosophila.biomedtzc.cn.
© The Author(s) 2020. Published by Oxford University Press.

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Year:  2020        PMID: 32103267      PMCID: PMC7044104          DOI: 10.1093/database/baaa005

Source DB:  PubMed          Journal:  Database (Oxford)        ISSN: 1758-0463            Impact factor:   3.451


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