Authors:
Sofia Startceva
;
Jerome G. Chandraseelan
;
Ari Visa
and
Andre S. Ribeiro
Affiliation:
Tampere University of Technology, Finland
Keyword(s):
Fluorescence-tagged RNA Quantification, Single-molecule Time-lapse Microscopy, Biosignal Processing.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Detection and Identification
;
Medical Image Detection, Acquisition, Analysis and Processing
;
Physiological Processes and Bio-Signal Modeling, Non-Linear Dynamics
Abstract:
We present a new quantitative method of estimation of fluorescent molecule numbers from time-lapse,
single-cell, fluorescence microscopy data. Its main aim is to eradicate backward propagation of noise, which
is present in previous methods. The method is first validated using Monte Carlo simulations. These tests
show that when the time-lapse data are corrupted with negative noise, the method obtains significantly more
precise results than current techniques. The applicability of the method is demonstrated on novel time-lapse,
single-cell measurements of fluorescently tagged ribonucleic acid (RNA) molecules. Interestingly, we find
that the intervals inferred by the new method have the same mean but reduced variability when compared to
the previously existing method, which, in accordance to human observers, is a more accurate estimation.