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ERN: Emerging Researchers National Conference in STEM

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Data Analytics for Nitric Oxide Biosensors

Undergraduate #69
Discipline: Mathematics and Statistics
Subcategory: Mathematics and Statistics

Deandria Harper - North Carolina Central University
Co-Author(s): Jonathan McDunn, Clinical Sensors, Inc. 2 Davis Dr, RTP N.C.



The development of technologies to improve point of care diagnostics will provide benefit for many patients and medical professionals. The company Clinical Sensors is contributing to this technology by developing nitric oxide sensors. An integral part of the sensors’ development is the data analysis. Data analysis will be performed by automated scripts written in the R programming language. The script is currently outputting statistical data summaries, graphs, and peak values. Updates to the program will further refine and summarize the outputs.

Funder Acknowledgement(s): NFS-1238547

Faculty Advisor: Dr. Caesar Jackson, crjackson@nccu.edu

Role: Statistical analysis using R programming language.

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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