A top-down approach to enhance the power of predicting human protein subcellular localization: Hum-mPLoc 2.0
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iNitro-Tyr: prediction of nitrotyrosine sites in proteins with general pseudo amino acid compositioniCTX-type: a sequence-based predictor for identifying the types of conotoxins in targeting ion channelsA multi-label predictor for identifying the subcellular locations of singleplex and multiplex eukaryotic proteinsReverse Engineering of Genome-wide Gene Regulatory Networks from Gene Expression DataGene ontology based transfer learning for protein subcellular localizationPredicting human protein subcellular localization by heterogeneous and comprehensive approaches.iDNA-Prot|dis: identifying DNA-binding proteins by incorporating amino acid distance-pairs and reduced alphabet profile into the general pseudo amino acid compositionAn ensemble classifier for eukaryotic protein subcellular location prediction using gene ontology categories and amino acid hydrophobicityImbalanced multi-modal multi-label learning for subcellular localization prediction of human proteins with both single and multiple sites.Multi-label multi-kernel transfer learning for human protein subcellular localization.An ensemble method for predicting subnuclear localizations from primary protein structures.A novel approach for protein subcellular location prediction using amino acid exposure.SPiCE: a web-based tool for sequence-based protein classification and explorationBioimaging-based detection of mislocalized proteins in human cancers by semi-supervised learning.Systems Biology Approaches for the Prediction of Possible Role of Chlamydia pneumoniae Proteins in the Etiology of Lung Cancer.Sparse regressions for predicting and interpreting subcellular localization of multi-label proteinsIdentifying the missing proteins in human proteome by biological language modelPredicting Subcellular Localization of Apoptosis Proteins Combining GO Features of Homologous Proteins and Distance Weighted KNN Classifier.iRSpot-TNCPseAAC: identify recombination spots with trinucleotide composition and pseudo amino acid componentsiNR-Drug: predicting the interaction of drugs with nuclear receptors in cellular networking.Energy matters: mitochondrial proteomics for biomedicine.Recent progress in predicting protein sub-subcellular locations.Some remarks on predicting multi-label attributes in molecular biosystems.Predicting multisite protein subcellular locations: progress and challenges.Protein subcellular multi-localization prediction using a min-max modular support vector machine.Predicting human protein subcellular locations by the ensemble of multiple predictors via protein-protein interaction network with edge clustering coefficients.pLoc-mPlant: predict subcellular localization of multi-location plant proteins by incorporating the optimal GO information into general PseAAC.Hum-mPLoc 3.0: prediction enhancement of human protein subcellular localization through modeling the hidden correlations of gene ontology and functional domain features.WegoLoc: accurate prediction of protein subcellular localization using weighted Gene Ontology terms.HPSLPred: An ensemble multi-label classifier for human protein subcellular location prediction with imbalanced source.MultiP-Apo: A Multilabel Predictor for Identifying Subcellular Locations of Apoptosis Proteins.A tale of two glutaminases: homologous enzymes with distinct roles in tumorigenesis.Protein (multi-)location prediction: using location inter-dependencies in a probabilistic frameworkComparative analysis of an experimental subcellular protein localization assay and in silico prediction methods.Human Protein Subcellular Localization with Integrated Source and Multi-label Ensemble ClassifierIdentification of protein-protein binding sites by incorporating the physicochemical properties and stationary wavelet transforms into pseudo amino acid composition.iATC-mHyb: a hybrid multi-label classifier for predicting the classification of anatomical therapeutic chemicals.Pyruvate kinase M knockdown-induced signaling via AMP-activated protein kinase promotes mitochondrial biogenesis, autophagy, and cancer cell survival.ProSim: A Method for Prioritizing Disease Genes Based on Protein Proximity and Disease Similarity.iLoc-Hum: using the accumulation-label scale to predict subcellular locations of human proteins with both single and multiple sites.
P2860
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P2860
A top-down approach to enhance the power of predicting human protein subcellular localization: Hum-mPLoc 2.0
description
2009 nî lūn-bûn
@nan
2009 թուականի Նոյեմբերին հրատարակուած գիտական յօդուած
@hyw
2009 թվականի նոյեմբերին հրատարակված գիտական հոդված
@hy
2009年の論文
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2009年論文
@yue
2009年論文
@zh-hant
2009年論文
@zh-hk
2009年論文
@zh-mo
2009年論文
@zh-tw
2009年论文
@wuu
name
A top-down approach to enhance ...... ar localization: Hum-mPLoc 2.0
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A top-down approach to enhance ...... ar localization: Hum-mPLoc 2.0
@en
A top-down approach to enhance ...... ar localization: Hum-mPLoc 2.0
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A top-down approach to enhance ...... ar localization: Hum-mPLoc 2.0
@ast
A top-down approach to enhance ...... ar localization: Hum-mPLoc 2.0
@en
A top-down approach to enhance ...... ar localization: Hum-mPLoc 2.0
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A top-down approach to enhance ...... ar localization: Hum-mPLoc 2.0
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A top-down approach to enhance ...... ar localization: Hum-mPLoc 2.0
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A top-down approach to enhance ...... ar localization: Hum-mPLoc 2.0
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P3181
P356
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A top-down approach to enhance ...... ar localization: Hum-mPLoc 2.0
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P304
P3181
P356
10.1016/J.AB.2009.07.046
P407
P577
2009-11-15T00:00:00Z