An image-based multi-label human protein subcellular localization predictor (iLocator) reveals protein mislocalizations in cancer tissues.

ABSTRACT:

Motivation

Human cells are organized into compartments of different biochemical cellular processes. Having proteins appear at the right time to the correct locations in the cellular compartments is required to conduct their functions in normal cells, whereas mislocalization of proteins can result in pathological diseases, including cancer.

Results

To reveal the cancer-related protein mislocalizations, we developed an image-based multi-label subcellular location predictor, iLocator, which covers seven cellular localizations. The iLocator incorporates both global and local image descriptors and generates predictions by using an ensemble multi-label classifier. The algorithm has the ability to treat both single- and multiple-location proteins. We first trained and tested iLocat

SUBMITTER: Xu YY 

PROVIDER: S-EPMC3722518 | biostudies-literature | 2013 Aug

REPOSITORIES: biostudies-literature