Assignment of unimodal probability distribution models for quantitative morphological phenotyping.

ABSTRACT:

Background

Cell morphology is a complex and integrative readout, and therefore, an attractive measurement for assessing the effects of genetic and chemical perturbations to cells. Microscopic images provide rich information on cell morphology; therefore, subjective morphological features are frequently extracted from digital images. However, measured datasets are fundamentally noisy; thus, estimation of the true values is an ultimate goal in quantitative morphological phenotyping. Ideal image analyses require precision, such as proper probability distribution analyses to detect subtle morphological changes, recall to minimize artifacts due to experimental error, and reproducibility to confirm the results.

Results

Here, we present UNIMO (UNImodal MOrphological data), a reliab

SUBMITTER: Ghanegolmohammadi F 

PROVIDER: S-EPMC8969357 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature