Automated analysis of protein subcellular location in time series images | Zendy

Yanhua Hu | Zendy; Elvira Osuna-Highley | Zendy; Juchang Hua | Zendy; Theodore S. Nowicki | Zendy; Robert Stolz | Zendy; Camille A. McKayle | Zendy; Robert F. Murphy | Zendy

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Automated analysis of protein subcellular location in time series images

Author(s) -

Yanhua Hu,

Elvira Osuna-Highley,

Juchang Hua,

Theodore S. Nowicki,

Robert Stolz,

Camille A. McKayle,

Robert F. Murphy

Publication year - 2010

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btq239

Subject(s) - computer science , artificial intelligence , pattern recognition (psychology) , segmentation , software , feature (linguistics) , autoregressive model , computer vision , time series , machine learning , mathematics , philosophy , linguistics , econometrics , programming language

Image analysis, machine learning and statistical modeling have become well established for the automatic recognition and comparison of the subcellular locations of proteins in microscope images. By using a comprehensive set of features describing static images, major subcellular patterns can be distinguished with near perfect accuracy. We now extend this work to time series images, which contain both spatial and temporal information. The goal is to use temporal features to improve recognition of protein patterns that are not fully distinguishable by their static features alone.

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