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Computational Approaches for Human Disease Gene Prediction and Ranking

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Systems Analysis of Human Multigene Disorders

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 799))

Abstract

While candidate gene association studies continue to be the most practical and frequently employed approach in disease gene investigation for complex disorders, selecting suitable genes to test is a challenge. There are several computational approaches available for selecting and prioritizing disease candidate genes. A majority of these tools are based on guilt-by-association principle where novel disease candidate genes are identified and prioritized based on either functional or topological similarity to known disease genes. In this chapter we review the prioritization criteria and the algorithms along with some use cases that demonstrate how these tools can be used for identifying and ranking human disease candidate genes.

Cheng Zhu and Chao Wu contributed equally to this work.

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    Authors and Affiliations

    1. Department of Computer Science, College of Engineering and Applied Science, University of Cincinnati, Cincinnati, OH, USA

      Cheng Zhu & Chao Wu

    2. Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, 3333 Burnet Ave. – MLC 7024, Cincinnati, OH, 45229-3039, USA

      Cheng Zhu, Chao Wu, Bruce J. Aronow & Anil G. Jegga D.V.M., M.S.

    3. Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45229, USA

      Bruce J. Aronow & Anil G. Jegga D.V.M., M.S.

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    1. Cheng Zhu
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    Correspondence to Anil G. Jegga D.V.M., M.S. .

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    1. University of Chicago, Chicago, Illinois, USA

      Natalia Maltsev

    2. University of Chicago, Chicago, Illinois, USA

      Andrey Rzhetsky

    3. University of Chicago, Chicago, Illinois, USA

      T. Conrad Gilliam

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    Zhu, C., Wu, C., Aronow, B.J., Jegga, A.G. (2014). Computational Approaches for Human Disease Gene Prediction and Ranking. In: Maltsev, N., Rzhetsky, A., Gilliam, T. (eds) Systems Analysis of Human Multigene Disorders. Advances in Experimental Medicine and Biology, vol 799. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8778-4_4

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