title: A dynamic data-driven framework for biological data using 2D barcodes.
abstract: 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.
authors.affiliation: Department of Systems and Computer Science, Howard University, Washington, DC 20059, USA. hli3302@gmail.com
authors.forename: Hui
authors.initials: H
authors.lastname: Li
authors.forename: Chunmei
authors.initials: C
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D000818:Animals; D019295:Computational Biology / Q000295:instrumentation / Q000379:methods*; D003198:Computer Simulation; D001330:Electronic Data Processing / Q000295:instrumentation*; D006801:Humans; D015233:Models, Statistical; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted