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Visualizing the Protein Sequence Universe
Author(s) -
Stanberry Larissa,
Higdon Roger,
Haynes Winston,
Kolker Natali,
Broomall William,
Ekanayake Saliya,
Hughes Adam,
Ruan Yang,
Qiu Judy,
Kolker Eugene,
Fox Geoffrey
Publication year - 2013
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.3072
Subject(s) - annotation , visualization , computer science , bottleneck , cyberinfrastructure , scalability , sequence (biology) , sequence space , similarity (geometry) , set (abstract data type) , data science , interpolation (computer graphics) , bootstrapping (finance) , data mining , information retrieval , biology , artificial intelligence , database , programming language , mathematics , pure mathematics , banach space , image (mathematics) , econometrics , embedded system , genetics , motion (physics)
SUMMARY Modern biology is experiencing a rapid increase in data volumes that challenges our analytical skills and existing cyberinfrastructure. Exponential expansion of the protein sequence universe (PSU), the protein sequence space, together with the costs and complexities of manual curation creates a major bottleneck in life sciences research. Existing resources lack scalable visualization tools that are instrumental for functional annotation. Here, we describe a new visualization tool using multidimensional scaling to create a 3D embedding of the protein space. The advantages of the proposed PSU method include the ability to scale to large numbers of sequences, integrate different similarity measures with other functional and experimental data, and facilitate protein annotation. We applied the method to visualize the prokaryotic PSU using sequence alignment scores. As an annotation example, we used the interpolation approach to map the set of annotated archaeal proteins into the prokaryotic PSU. Transdisciplinary approaches akin to the one described in this paper are urgently needed to quickly and efficiently translate the influx of new data into tangible innovations and groundbreaking discoveries. Copyright © 2013 John Wiley & Sons, Ltd.