Preparing your results

Our searching services are busy right now. Your search will reload in five seconds.

X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

CellCognition: time-resolved phenotype annotation in high-throughput live cell imaging.

Nature methods | Sep 31, 2010

Fluorescence time-lapse imaging has become a powerful tool to investigate complex dynamic processes such as cell division or intracellular trafficking. Automated microscopes generate time-resolved imaging data at high throughput, yet tools for quantification of large-scale movie data are largely missing. Here we present CellCognition, a computational framework to annotate complex cellular dynamics. We developed a machine-learning method that combines state-of-the-art classification with hidden Markov modeling for annotation of the progression through morphologically distinct biological states. Incorporation of time information into the annotation scheme was essential to suppress classification noise at state transitions and confusion between different functional states with similar morphology. We demonstrate generic applicability in different assays and perturbation conditions, including a candidate-based RNA interference screen for regulators of mitotic exit in human cells. CellCognition is published as open source software, enabling live-cell imaging-based screening with assays that directly score cellular dynamics.

Pubmed ID: 20693996 RIS Download

Mesh terms: Artificial Intelligence | Automation | Cell Shape | Cell Survival | Cells | Computational Biology | Computer Simulation | Fluorescence | HeLa Cells | Humans | Image Processing, Computer-Assisted | Kinetics | Markov Chains | Mitosis | Molecular Imaging | Phenotype | Software | Time Factors

Research resources used in this publication

None found

Research tools detected in this publication

None found

Data used in this publication

None found

Associated grants

None

Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.