Clustering of Bacterial Growth Dynamics in Response to Growth Media by Dynamic Time Warping.

ABSTRACT: Bacterial growth curves, representing population dynamics, are still poorly understood. The growth curves are commonly analyzed by model-based theoretical fitting, which is limited to typical S-shape fittings and does not elucidate the dynamics in their entirety. Thus, whether a certain growth condition results in any particular pattern of growth curve remains unclear. To address this question, up-to-date data mining techniques were applied to bacterial growth analysis for the first time. Dynamic time warping (DTW) and derivative DTW (DDTW) were used to compare the similarity among 1015 growth curves of 28 Escherichia coli strains growing in three different media. In the similarity evaluation, agglomerative hierarchical clustering, assessed with four statistic benchmarks, successfully cate

SUBMITTER: Cao YY 

PROVIDER: S-EPMC7143780 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature