Temporal classification of short time series data.

ABSTRACT:

Motivation

Within the frame of their genetic capacity, organisms are able to modify their molecular state to cope with changing environmental conditions or induced genetic disposition. As high throughput methods are becoming increasingly affordable, time series analysis techniques are applied frequently to study the complex dynamic interplay between genes, proteins, and metabolites at the physiological and molecular level. Common analysis approaches fail to simultaneously include (i) information about the replicate variance and (ii) the limited number of responses/shapes that a biological system is typically able to take.

Results

We present a novel approach to model and classify short time series signals, conceptually based on a classical time series analysis, where the depe

SUBMITTER: Venn B 

PROVIDER: S-EPMC10792935 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature