Studying molecular motor-based cargo transport: What is real and what is noise?

Dmitri Y. Petrov, Roop Mallik, George T. Shubeita, Michael Vershinin, Steven P. Gross, Clare C. Yu

Research output: Contribution to journalArticle

Abstract

Noise is a major problem in analyzing tracking data of cargos moved by molecular motors. We use Bayesian statistics to incorporate what is known about the noise in parsing the trajectory of a cargo into a series of constant velocity segments. Tracks with just noise and no underlying motion are fit with constant velocity segments to produce a calibration curve of fit quality versus average segment duration. Fits to tracks of moving cargos are compared to the calibration curves with similar noise. The fit with the optimum number of constant velocity states has the least number of segments needed to match the fit quality of the calibration curve. We have tested this approach using tracks with known underlying motion generated by computer simulations and with a specially designed in vitro experiment. We present the results of using this parsing approach to analyze transport of lipid droplets in Drosophila embryos.

Original languageEnglish (US)
Pages (from-to)2953-2963
Number of pages11
JournalBiophysical journal
Volume92
Issue number8
DOIs
StatePublished - Apr 2007

ASJC Scopus subject areas

  • Biophysics

Fingerprint Dive into the research topics of 'Studying molecular motor-based cargo transport: What is real and what is noise?'. Together they form a unique fingerprint.

  • Cite this