title: Classification of biosensor time series using dynamic time warping: applications in screening cancer cells with characteristic biomarkers.
abstract: The development of biosensors that produce time series data will facilitate improvements in biomedical diagnostics and in personalized medicine. The time series produced by these devices often contains characteristic features arising from biochemical interactions between the sample and the sensor. To use such characteristic features for determining sample class, similarity-based classifiers can be utilized. However, the construction of such classifiers is complicated by the variability in the time domains of such series that renders the traditional distance metrics such as Euclidean distance ineffective in distinguishing between biological variance and time domain variance. The dynamic time warping (DTW) algorithm is a sequence alignment algorithm that can be used to align two or more series to facilitate quantifying similarity. In this article, we evaluated the performance of DTW distance-based similarity classifiers for classifying time series that mimics electrical signals produced by nanotube biosensors. Simulation studies demonstrated the positive performance of such classifiers in discriminating between time series containing characteristic features that are obscured by noise in the intensity and time domains. We then applied a DTW distance-basedk-nearest neighbors classifier to distinguish the presence/absence of mesenchymal biomarker in cancer cells in buffy coats in a blinded test. Using a train-test approach, we find that the classifier had high sensitivity (90.9%) and specificity (81.8%) in differentiating between EpCAM-positive MCF7 cells spiked in buffy coats and those in plain buffy coats.
authors.affiliation: Biostatistics Shared Facility, JG Brown Cancer Center, University of Louisville, KY, USA; Department of Bioinformatics and Biostatistics, University of Louisville, KY, USA.
authors.forename: Shesh N
authors.initials: SN
authors.lastname: Rai
authors.affiliation: Department of Bioinformatics and Biostatistics, University of Louisville, KY, USA; Department of Medicine, University of Louisville, KY, USA.
authors.forename: Patrick J
authors.initials: PJ
authors.lastname: Trainor
authors.affiliation: Small Systems Laboratory, Department of Mechanical Engineering, Worcester Polytechnic Institute, Worcester, MA.
authors.forename: Farhad
authors.initials: F
authors.lastname: Khosravi
authors.affiliation: Hematology and Oncology, James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA.
authors.forename: Goetz
authors.initials: G
authors.lastname: Kloecker
authors.affiliation: Small Systems Laboratory, Department of Mechanical Engineering, Worcester Polytechnic Institute, Worcester, MA.
authors.forename: Balaji
authors.initials: B
authors.lastname: Panchapakesan
keywords: MCF7; biosensors; breast cancer; buffy coats; cancer detection; epcam; instance-based learning; k-nn classifier; time series