HybridGO-Loc – Multi-Label Protein Subcellular Localization Prediction

HybridGO-Loc

:: DESCRIPTION

HybridGO-Loc stands for mining Hybrid features on Gene Ontology (GO) for protein subcellular Localization prediction, meaning that this predictor extracts the feature of proteins from different perspectives of GO information (i.e. GO frequency occurrences and GO semantic similarity) and then processes the information by a multi-label multi-class SVM classifier with an adaptive decision scheme.

::DEVELOPER

Dr. Man-Wai Mak

:: SCREENSHOTS

N/A

::REQUIREMENTS

Web browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

Wan S, Mak MW, Kung SY.
HybridGO-Loc: mining hybrid features on gene ontology for predicting subcellular localization of multi-location proteins.
PLoS One. 2014 Mar 19;9(3):e89545. doi: 10.1371/journal.pone.0089545. PMID: 24647341; PMCID: PMC3960097.

iLocator – An Image-based Multi-label Human Protein Subcellular Localization Predictor

iLocator

:: DESCRIPTION

iLocator is an image-based multi-label subcellular location predictor, which covers 7 cellular localizations, i.e. cytoplasm, endoplasmic reticulum, Golgi apparatus, lysosome, mitochondria, nucleus, and vesicles. The iLocator incorporates both global and local image descriptors, and uses an ensemble multi-label classifier to generate accurate predictions.

::DEVELOPER

Computational Systems Biology Group, Shanghai Jiao Tong University

:: SCREENSHOTS

:: REQUIREMENTS

Windows
Matlab

:: DOWNLOAD

iLocator

:: MORE INFORMATION

Citation:

Bioinformatics. 2013 Aug 15;29(16):2032-40. doi: 10.1093/bioinformatics/btt320. Epub 2013 Jun 4.
An image-based multi-label human protein subcellular localization predictor (iLocator) reveals protein mislocalizations in cancer tissues.
Xu YY1, Yang F, Zhang Y, Shen HB.

mPLR-Loc – Multi-Label Protein Subcellular Localization Prediction

mPLR-Loc

:: DESCRIPTION

mPLR-Loc is an efficient multi-label predictor based on penalized logistic regression and adaptive decisions for predicting both single- and multi-location proteins.

::DEVELOPER

Dr. Man-Wai Mak

:: SCREENSHOTS

N/A

::REQUIREMENTS

Web browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

Anal Biochem. 2015 Mar 15;473:14-27. doi: 10.1016/j.ab.2014.10.014. Epub 2014 Oct 31.
mPLR-Loc: an adaptive decision multi-label classifier based on penalized logistic regression for protein subcellular localization prediction.
Wan S, Mak MW, Kung SY.

R3P-Loc – Multi-Label Protein Subcellular Localization Prediction

R3P-Loc

:: DESCRIPTION

R3P-Loc stands for Ridge Regression and Random Projection for protein subcellular Localization prediction, meaning that this predictor applies random projection to reduce the feature dimensions of an ensemble ridge regression classifier.

::DEVELOPER

Dr. Man-Wai Mak

:: SCREENSHOTS

N/A

::REQUIREMENTS

Web browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

J Theor Biol. 2014 Nov 7;360:34-45. doi: 10.1016/j.jtbi.2014.06.031. Epub 2014 Jul 2.
R3P-Loc: a compact multi-label predictor using ridge regression and random projection for protein subcellular localization.
Wan S, Mak MW, Kung SY.