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iLoc-Plant specifications

Information


Unique identifier OMICS_01624
Name iLoc-Plant
Interface Web user interface
Restrictions to use None
Input data Some sequences of query proteins.
Input format FASTA
Computer skills Basic
Stability Stable
Maintained Yes

Maintainer


  • person_outline Xuan Xiao

Additional information


http://www.jci-bioinfo.cn/bioinfo/wzc/subcellular/readme/Plant.jsp

Publication for iLoc-Plant

iLoc-Plant citations

 (3)
library_books

Predicting Subcellular Localization of Apoptosis Proteins Combining GO Features of Homologous Proteins and Distance Weighted KNN Classifier

2016
Biomed Res Int
PMCID: 4860209
PMID: 27213149
DOI: 10.1155/2016/1793272

[…] eresting because they may have some very special biological functions intriguing to investigators in both basic research and drug discovery. So far, many outstanding predictors, that is, iLoc-Euk [], iLoc-Plant [], MLPred-Euk [], MultiP-SChlo [], mGOASVM [], and HybridGO-Loc [], were also developed into web-servers used to cope with the multiple location problems in eukaryotic, plant, virus, and h […]

library_books

Identification and characterization of plastid type proteins from sequence attributed features using machine learning

2013
BMC Bioinformatics
PMCID: 3851450
PMID: 24266945
DOI: 10.1186/1471-2105-14-S14-S7

[…] our phase-I models in distinguishing the plastid vs. non-plastid proteins with two widely used tools TargetP [] and WoLF PSORT [] along with two other recently developed predictors; YLoc-HiRes [] and iLoc-Plant []. The performance of these methods was compared using the same independent dataset containing 316 plastid and 316 non-plastid proteins (Table ). As both DIPEP and NCC models from our phas […]

library_books

Imbalanced Multi Modal Multi Label Learning for Subcellular Localization Prediction of Human Proteins with Both Single and Multiple Sites

2012
PLoS One
PMCID: 3371015
PMID: 22715364
DOI: 10.1371/journal.pone.0037155

[…] ed YLoc by using the simple naive Bayes classifier. Lin et al. proposed a knowledge based approach by using the local sequence similarity. Recently, four new approaches called iLoc-Euk , iLoc-Gneg , iLoc-Plant and iLoc-Virus were proposed based on a multi-label classifier to predict the subcellular locations of eukaryotic, Gram-negative bacterial, plant, and virus proteins, respectively. In , W […]

Citations

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iLoc-Plant institution(s)
Computer Department, Jing-De-Zhen Ceramic Institute, Jing-De-Zhen, China; Gordon Life Science Institute, San Diego, CA, USA
iLoc-Plant funding source(s)
Supported by the grants from the National Natural Science Foundation of China (No. 60961003), the Natural Science Foundation of Jiangxi Province, China (2010GQS0127), the Key Project of Chinese Ministry of Education (No. 210116), the Province National Natural Science Foundation of Jiang Xi (2009GZS0064), the Department of Education of Jiang-Xi Province (No. GJJ09271), and the plan for training youth scientists (stars of Jing-Gang) of Jiangxi Province.

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