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      Coral: Clear and customizable visualization of human kinome data

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          SUMMARY

          Protein kinases represent one of the largest gene families in eukaryotes and play roles in a wide range of cell signaling processes and human diseases. Current tools for visualizing kinase data in the context of the human kinome superfamily are limited to encoding data through the addition of nodes to a low-resolution image of the kinome tree. We present Coral, a user-friendly interactive web application for visualizing both quantitative and qualitative data. Unlike previous tools, Coral can encode data in three features (node color, node size, and branch color), allows three modes of kinome visualization (the traditional kinome tree as well as radial and dynamic force networks) and generates high-resolution scalable vector graphic files suitable for publication without the need for refinement in graphic editing software. Due to its user-friendly, interactive, and highly customizable design, Coral is broadly applicable to high-throughput studies of the human kinome. The source code and web application are available at github.com/dphansti/Coral.html and phanstiel-lab.med.unc.edu/Coral respectively.

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          Author and article information

          Journal
          101656080
          43733
          Cell Syst
          Cell Syst
          Cell systems
          2405-4712
          2405-4720
          12 October 2018
          29 August 2018
          26 September 2018
          26 September 2019
          : 7
          : 3
          : 347-350.e1
          Affiliations
          [1 ]Curriculum in Genetics & Molecular Biology, University of North Carolina, Chapel Hill, NC 27599, USA
          [2 ]These authors contributed equally
          [3 ]Thurston Arthritis Research Center, University of North Carolina, Chapel Hill, NC 27599, USA
          [4 ]Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill and North Carolina State University, Chapel Hill, NC 27514, USA
          [5 ]Department of Pharmacology, University of North Carolina, Chapel Hill, NC 27599, USA
          [6 ]Curriculum in Bioinformatics & Computational Biology, University of North Carolina, Chapel Hill, NC 27599, USA
          [7 ]Department of Microbiology and Immunology, Medical University of South Carolina, Charleston, SC 29425, USA
          [8 ]Department of Cell Biology & Physiology, University of North Carolina, Chapel Hill, NC 27599, USA
          [9 ]Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA
          [10 ]Lead Contact
          Author notes

          AUTHOR CONTRIBUTIONS

          Conceptualization: D.H.P.

          Software: D.H.P., E.M.D., M.E.B, B.A.A., I.J.R., and K.S.M.

          Writing: K.S.M. and D.H.P.

          Visualization: E.M.D.

          Supervision: D.H.P.

          Resources: D.H.P., S.M.G, and J.H.

          Article
          PMC6366324 PMC6366324 6366324 nihpa992164
          10.1016/j.cels.2018.07.001
          6366324
          30172842
          a6ba1c35-eb47-4782-aeb0-5b09e6d5e3c3
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