TY - JOUR
T1 - Instruction tools for signal processing and machine learning for ion-channel sensors
AU - Sattigeri, Prasanna
AU - Thiagarajan, Jayaraman
AU - Ramamurthy, Karthikeyan
AU - Spanias, Andreas
AU - Banavar, Mahesh
AU - Dixit, Abhinav
AU - Fan, Jie
AU - Malu, Mohit
AU - Jaskie, Kristen
AU - Rao, Sunil
AU - Shanthamallu, Uday
AU - Narayanaswamy, Vivek
AU - Katoch, Sameeksha
N1 - Publisher Copyright:
© 2022 IGI Global. All rights reserved.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - Ion-Channel Signal
KW - JDSP
KW - Signal Processing
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U2 - 10.4018/IJVPLE.285601
DO - 10.4018/IJVPLE.285601
M3 - Article
AN - SCOPUS:85149987030
SN - 1947-8518
VL - 12
JO - International Journal of Virtual and Personal Learning Environments
JF - International Journal of Virtual and Personal Learning Environments
IS - 1
ER -