Data Like This: Ranked Search of Genomic Data Vision Paper
Published In
Proceedings of the Second International Workshop on Exploratory Search in Databases and the Web
Document Type
Citation
Publication Date
2015
Subjects
Information retrieval, Database management, Data mining
Abstract
High-throughput genetic sequencing produces the ultimate "big data": a human genome sequence contains more than 3B base pairs, and more and more characteristics, or annotations, are being recorded at the base-pair level. Locating areas of interest within the genome is a challenge for researchers, limiting their investigations. We describe our vision of adapting "big data" ranked search to the problem of searching the genome. Our goal is to make searching for data as easy for scientists as searching the Internet.
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Unaffiliated researchers can access the work here: http://dx.doi.org/10.1145/2795218.2795221
DOI
10.1145/2795218.2795221
Persistent Identifier
http://archives.pdx.edu/ds/psu/20875
Citation Details
V. M. Megler, David Maier, Daniel Bottomly, Libbey White, Shannon McWeeney, and Beth Wilmot. 2015. Data Like This: Ranked Search of Genomic Data Vision Paper. In Proceedings of the Second International Workshop on Exploratory Search in Databases and the Web (ExploreDB '15), Georgia Koutrika, Laks V. S. Lakshmanan, Mirek Riedewald, and Kostas Stefanidis (Eds.). ACM, New York, NY, USA, 3-5.