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Strategic Integration of Multiple Bioinformatics Resources for System Level Analysis of Biological Networks

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Biological Networks and Pathway Analysis

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1613))

Abstract

Recent technological advances in genomics allow the production of biological data at unprecedented tera- and petabyte scales. Efficient mining of these vast and complex datasets for the needs of biomedical research critically depends on a seamless integration of the clinical, genomic, and experimental information with prior knowledge about genotype-phenotype relationships. Such experimental data accumulated in publicly available databases should be accessible to a variety of algorithms and analytical pipelines that drive computational analysis and data mining.

We present an integrated computational platform Lynx (Sulakhe et al., Nucleic Acids Res 44:D882–D887, 2016) ( http://lynx.cri.uchicago.edu ), a web-based database and knowledge extraction engine. It provides advanced search capabilities and a variety of algorithms for enrichment analysis and network-based gene prioritization. It gives public access to the Lynx integrated knowledge base (LynxKB) and its analytical tools via user-friendly web services and interfaces. The Lynx service-oriented architecture supports annotation and analysis of high-throughput experimental data. Lynx tools assist the user in extracting meaningful knowledge from LynxKB and experimental data, and in the generation of weighted hypotheses regarding the genes and molecular mechanisms contributing to human phenotypes or conditions of interest. The goal of this integrated platform is to support the end-to-end analytical needs of various translational projects.

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Author information

Authors and Affiliations

  1. Department of Human Genetics, University of Chicago, 920 E. 58th Street, Chicago, IL, 60637, USA

    Mark D’Souza, Dinanath Sulakhe, Sheng Wang, Bing Xie, Andrew Taylor, T. Conrad Gilliam & Natalia Maltsev

  2. Argonne National Laboratory, Building 221, Room: A142, 9700 South Cass Avenue, Argonne, IL, 60439, USA

    Mark D’Souza

  3. Computation Institute, University of Chicago, 5735 S. Ellis Avenue, Chicago, IL, 60637, USA

    Dinanath Sulakhe, T. Conrad Gilliam & Natalia Maltsev

  4. Toyota Technological Institute at Chicago, 6045 S. Kenwood Avenue, Chicago, IL, 60637, USA

    Sheng Wang & Somaye Hashemifar

  5. Department of Computer Science, Illinois Institute of Technology, Chicago, IL, 60616, USA

    Bing Xie

  6. Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America, Department of Energy Joint Genome Institute, Walnut Creek, CA, USA

    Inna Dubchak

Authors
  1. Mark D’Souza
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  2. Dinanath Sulakhe
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  3. Sheng Wang
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  4. Bing Xie
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  5. Somaye Hashemifar
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  6. Andrew Taylor
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  7. Inna Dubchak
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  8. T. Conrad Gilliam
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  9. Natalia Maltsev
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Correspondence to Mark D’Souza .

Editor information

Editors and Affiliations

  1. Keck School of Medicine, University of Southern California, Los Angeles, California, USA

    Tatiana V. Tatarinova

  2. Prosapia Genetics, Solana Beach, California, USA

    Yuri Nikolsky

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D’Souza, M. et al. (2017). Strategic Integration of Multiple Bioinformatics Resources for System Level Analysis of Biological Networks. In: Tatarinova, T., Nikolsky, Y. (eds) Biological Networks and Pathway Analysis. Methods in Molecular Biology, vol 1613. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7027-8_5

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  • DOI: https://doi.org/10.1007/978-1-4939-7027-8_5

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7025-4

  • Online ISBN: 978-1-4939-7027-8

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