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Network-Based Gene Function Prediction in Mouse and Other Model Vertebrates Using MouseNet Server

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Protein Function Prediction

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1611))

Abstract

The mouse, Mus musculus, is a popular model organism for the study of human genes involved in development, immunology, and disease phenotypes. Despite recent revolutions in gene-knockout technologies in mouse, identification of candidate genes for functions of interest can further accelerate the discovery of novel gene functions. The collaborative nature of genetic functions allows for the inference of gene functions based on the principle of guilt-by-association. Genome-scale co-functional networks could therefore provide functional predictions for genes via network analysis. We recently constructed such a network for mouse (MouseNet), which interconnects over 88% of protein-coding genes with 788,080 functional relationships. The companion web server (www.inetbio.org/mousenet) enables researchers with no bioinformatics expertise to generate predictions that facilitate discovery of novel gene functions. In this chapter, we present the theoretical framework for MouseNet, as well as step-by-step instructions and technical tips for functional prediction of genes and pathways in mouse and other model vertebrates.

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Acknowledgments

This work was supported by grants from the National Research Foundation of Korea (2015R1A2A1A15055859, 2012M3A9B4028641, 2012M3A9C7050151).

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Authors and Affiliations

  1. Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea

    Eiru Kim & Insuk Lee

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  1. Eiru Kim
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  2. Insuk Lee
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Correspondence to Insuk Lee .

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Editors and Affiliations

  1. Department of Biological Sciences and Computer Science, Purdue University, West Lafayette, Indiana, USA

    Daisuke Kihara

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Kim, E., Lee, I. (2017). Network-Based Gene Function Prediction in Mouse and Other Model Vertebrates Using MouseNet Server. In: Kihara, D. (eds) Protein Function Prediction. Methods in Molecular Biology, vol 1611. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7015-5_14

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  • DOI: https://doi.org/10.1007/978-1-4939-7015-5_14

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7013-1

  • Online ISBN: 978-1-4939-7015-5

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