Closed-form density-based framework for automatic detection of cellular morphology changes.

ABSTRACT: A primary method for studying cellular function is to examine cell morphology after a given manipulation. Fluorescent markers attached to proteins/intracellular structures of interest in conjunction with 3D fluorescent microscopy are frequently exploited for functional analysis. Despite the central role of morphology comparisons in cell biological approaches, few statistical tools are available that allow biological scientists without a high level of statistical training to quantify the similarity or difference of fluorescent images containing multifactorial information. We transform intracellular structures into kernels and develop a multivariate two-sample test that is nonparametric and asymptotically normal to directly and quantitatively compare cellular morphologies. The asymptotic nor

SUBMITTER: Duong T 

PROVIDER: S-EPMC3365204 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature