ERIC Number: EJ1349110
Record Type: Journal
Publication Date: 2022
Pages: 17
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1947-8518
EISSN: EISSN-1947-8526
Instruction Tools for Signal Processing and Machine Learning for Ion-Channel Sensors
Sattigeri, Prasanna; Thiagarajan, Jayaraman; Ramamurthy, Karthikeyan; Spanias, Andreas; Banavar, Mahesh; Dixit, Abhinav; Fan, Jie; Malu, Mohit; Jaskie, Kristen; Rao, Sunil; Shanthamallu, Uday; Katoch, Sameeksha
International Journal of Virtual and Personal Learning Environments, v12 n1 2022
Ion channel sensors have several applications including DNA sequencing, biothreat detection, and medical applications. Ion channel sensors mimic the selective transport mechanism of cell membranes and can detect a wide range of analytes at the molecule level. Analytes are sensed through changes in signal patterns. Papers in the literature have described different methods for ion channel signal analysis. In this paper, the authors describe a series of new graphical tools for ion channel signal analysis which can be used for research and education. The paper focuses on the utility of these tools in biosensor classes. Teaching signal processing and machine learning for ion channel sensors is challenging because of the multidisciplinary content and student backgrounds which include physics, chemistry, biology, and engineering. The paper describes graphical ion channel analysis tools developed for an online simulation environment called J-DSP. The tools are integrated and assessed in a graduate bio-sensor course through computer laboratory exercises.
Descriptors: Measurement Equipment, Artificial Intelligence, Biochemistry, Acoustics, Simulated Environment, Spectroscopy, Programming Languages, Computer Software, Engineering
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: National Science Foundation (NSF)
Authoring Institution: N/A
Grant or Contract Numbers: N/A