Predicting plant protein subcellular multi-localization by Chou's PseAAC formulation based multi-label homolog knowledge transfer learning
From MaRDI portal
Publication:292748
DOI10.1016/J.JTBI.2012.06.028zbMath1337.92065OpenAlexW1998291732WikidataQ34285299 ScholiaQ34285299MaRDI QIDQ292748
Publication date: 9 June 2016
Published in: Journal of Theoretical Biology (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jtbi.2012.06.028
multi-label learningnonparametric multiple kernel learningperformance overestimationprotein subcellular localizationtransfer learning
Related Items (13)
Linear regression model of short \(k\)-word: a similarity distance suitable for biological sequences with various lengths ⋮ iCDI-PseFpt: identify the channel-drug interaction in cellular networking with PseAAC and molecular fingerprints ⋮ Prediction of posttranslational modification sites from amino acid sequences with kernel methods ⋮ Robust feature generation for protein subchloroplast location prediction with a weighted GO transfer model ⋮ Naïve Bayes classifier with feature selection to identify phage virion proteins ⋮ Gram-positive and Gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou's general PseAAC ⋮ Human proteins characterization with subcellular localizations ⋮ An effective haplotype assembly algorithm based on hypergraph partitioning ⋮ pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC ⋮ iPPI-PseAAC(CGR): identify protein-protein interactions by incorporating chaos game representation into PseAAC ⋮ Machine learning approaches for discrimination of extracellular matrix proteins using hybrid feature space ⋮ R3P-Loc: a compact multi-label predictor using ridge regression and random projection for protein subcellular localization ⋮ Classification of membrane protein types using voting feature interval in combination with Chou's pseudo amino acid composition
Uses Software
Cites Work
- Unnamed Item
- Use of fuzzy clustering technique and matrices to classify amino acids and its impact to Chou's pseudo amino acid composition
- SubChlo: predicting protein subchloroplast locations with pseudo-amino acid composition and the evidence-theoretic \(K\)-nearest neighbor (ET-KNN) algorithm
- A novel feature representation method based on Chou's pseudo amino acid composition for protein structural class prediction
- Some remarks on protein attribute prediction and pseudo amino acid composition
- Using the concept of Chou's pseudo amino acid composition for risk type prediction of human papillomaviruses
- \textbf{iLoc-Virus}: a multi-label learning classifier for identifying the subcellular localization of virus proteins with both single and multiple sites
- Multi-kernel transfer learning based on Chou's PseAAC formulation for protein submitochondria localization
This page was built for publication: Predicting plant protein subcellular multi-localization by Chou's PseAAC formulation based multi-label homolog knowledge transfer learning
