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A Dynamic Data-Driven Framework for Biological Data Using 2D Barcodes
Author(s) -
Hui Li,
Chunmei Liu
Publication year - 2012
Publication title -
computational and mathematical methods in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.462
H-Index - 48
eISSN - 1748-6718
pISSN - 1748-670X
DOI - 10.1155/2012/892098
Subject(s) - barcode , computer science , flexibility (engineering) , scalability , biological data , data processing , data management , data mining , computer data storage , dynamic data , object (grammar) , distributed computing , real time computing , database , computer hardware , artificial intelligence , bioinformatics , statistics , mathematics , biology , operating system
Biology data is increasing exponentially from biological laboratories. It is a complicated problem for further processing the data. Processing computational data and data from biological laboratories manually may lead to potential errors in further analysis. In this paper, we proposed an efficient data-driven framework to inspect laboratory equipment and reduce impending failures. Our method takes advantage of the 2D barcode technology which can be installed on the specimen as a trigger for the data-driven system. For this end, we proposed a series of algorithms to speed up the data processing. The results show that the proposed system increases the system's scalability and flexibility. Also, it demonstrates the ability of linking a physical object with digital information to reduce the manual work related to experimental specimen. The characteristics such as high capacity of storage and data management of the 2D barcode technology provide a solution to collect experimental laboratory data in a quick and accurate fashion.

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